# AgentShelf - Complete Site Content > Generated: 2026-04-07T07:41:39.004Z > Source: https://agentshelf.ai > This file is auto-generated at build time from the current public site source content. This file contains the current public-facing site content for LLM consumption. --- ## Public Routes - https://agentshelf.ai - https://agentshelf.ai/discover - https://agentshelf.ai/about - https://agentshelf.ai/work-with-us - https://agentshelf.ai/blog - https://agentshelf.ai/technology/why-multi-agent - https://agentshelf.ai/technology/architecture - https://agentshelf.ai/technology/infrastructure - https://agentshelf.ai/llm.txt - https://agentshelf.ai/llms.txt - https://agentshelf.ai/.well-known/llms.txt - https://agentshelf.ai/llms-marketplace.txt - https://agentshelf.ai/llms-full.txt - https://agentshelf.ai/blog/best-practices-for-product-discovery-with-llm-agents - https://agentshelf.ai/blog/understanding-ai-agents-beyond-the-llm - https://agentshelf.ai/legal/privacy-policy - https://agentshelf.ai/legal/terms-and-conditions - https://agentshelf.ai/discover/customer-support-tier1 - https://agentshelf.ai/discover/knowledge-base - https://agentshelf.ai/discover/lead-enrichment - https://agentshelf.ai/discover/meeting-prep - https://agentshelf.ai/discover/alphafold-protein - https://agentshelf.ai/discover/alphafold-protein-structure-agent - https://agentshelf.ai/discover/apollo-enrichment - https://agentshelf.ai/discover/apolloio-enrichment-agent - https://agentshelf.ai/discover/artifact-builder - https://agentshelf.ai/discover/batch-enrichment-agent - https://agentshelf.ai/discover/biorxiv-preprint-agent - https://agentshelf.ai/discover/brand-guidelines - https://agentshelf.ai/discover/brand-guidelines-manager - https://agentshelf.ai/discover/browser-automation - https://agentshelf.ai/discover/browser-automation-engineer - https://agentshelf.ai/discover/canvas-designer - https://agentshelf.ai/discover/chembl-drug-discovery-agent - https://agentshelf.ai/discover/classification-agent - https://agentshelf.ai/discover/clinicaltrialsgov-agent - https://agentshelf.ai/discover/clinpgx-pharmacogenomics-agent - https://agentshelf.ai/discover/co-investor-discovery-agent - https://agentshelf.ai/discover/content-extractor-agent - https://agentshelf.ai/discover/context-analyzer-agent - https://agentshelf.ai/discover/conversation-manager-agent - https://agentshelf.ai/discover/crunchbase-api-agent - https://agentshelf.ai/discover/crunchbase-web-scraper - https://agentshelf.ai/discover/data-extraction-agent - https://agentshelf.ai/discover/data-validator-agent - https://agentshelf.ai/discover/data-visualization - https://agentshelf.ai/discover/data-visualization-specialist - https://agentshelf.ai/discover/deduplication-agent - https://agentshelf.ai/discover/document-specialist - https://agentshelf.ai/discover/enrichment-pipeline-agent - https://agentshelf.ai/discover/field-mapper-agent - https://agentshelf.ai/discover/generative-artist - https://agentshelf.ai/discover/geo-gene-expression-agent - https://agentshelf.ai/discover/gif-animator - https://agentshelf.ai/discover/gwas-catalog-agent - https://agentshelf.ai/discover/hmdb-metabolome-agent - https://agentshelf.ai/discover/internal-communications-specialist - https://agentshelf.ai/discover/ios-test-automation-engineer - https://agentshelf.ai/discover/kegg-pathway-agent - https://agentshelf.ai/discover/linkedin-profile-scraper - https://agentshelf.ai/discover/mcp-server-builder - https://agentshelf.ai/discover/merge-resolution-agent - https://agentshelf.ai/discover/metabolomics-workbench-agent - https://agentshelf.ai/discover/news-aggregator-agent - https://agentshelf.ai/discover/open-targets-drug-discovery-agent - https://agentshelf.ai/discover/pdb-protein-structure-agent - https://agentshelf.ai/discover/pdf-specialist - https://agentshelf.ai/discover/presentation-builder - https://agentshelf.ai/discover/prompt-builder-agent - https://agentshelf.ai/discover/pubchem-chemistry-agent - https://agentshelf.ai/discover/response-parser-agent - https://agentshelf.ai/discover/salesforce-apex-developer-agent - https://agentshelf.ai/discover/salesforce-bulk-data-agent - https://agentshelf.ai/discover/salesforce-code-review-agent - https://agentshelf.ai/discover/salesforce-custom-object-agent - https://agentshelf.ai/discover/salesforce-deployment-agent - https://agentshelf.ai/discover/salesforce-flow-builder-agent - https://agentshelf.ai/discover/salesforce-integration-agent - https://agentshelf.ai/discover/salesforce-lwc-developer-agent - https://agentshelf.ai/discover/salesforce-orchestrator-agent - https://agentshelf.ai/discover/salesforce-personaccount-agent - https://agentshelf.ai/discover/salesforce-planning-agent - https://agentshelf.ai/discover/salesforce-security-review-agent - https://agentshelf.ai/discover/salesforce-soql-agent - https://agentshelf.ai/discover/salesforce-test-class-agent - https://agentshelf.ai/discover/salesforce-trigger-agent - https://agentshelf.ai/discover/salesql-enrichment-agent - https://agentshelf.ai/discover/search-result-parser-agent - https://agentshelf.ai/discover/skill-creator - https://agentshelf.ai/discover/spreadsheet-analyst - https://agentshelf.ai/discover/summarization-agent - https://agentshelf.ai/discover/token-optimizer-agent - https://agentshelf.ai/discover/web-app-tester - https://agentshelf.ai/discover/web-asset-generator - https://agentshelf.ai/discover/web-security-analyst - https://agentshelf.ai/discover/website-content-scraper --- ## Homepage - Route: https://agentshelf.ai - SEO Title: AgentShelf.ai - Enterprise AI Agent Platform - SEO Description: Turn your best people's expertise into AI agents anyone on the team can use - no code, any model, enterprise-ready. ### Hero - Title: Your institutional knowledge. - Title Highlight: Every LLM's power. - Subtitle: Turn your best people's expertise into AI agents anyone on the team can use — no code, any model, enterprise-ready. - Trust Line: Built by operators from Axos Bank, Google, Bank of America, Comcast Voice AI #### CTA - Primary: Request Early Access - Secondary: Contact Sales ### Problem - Label: The problem - Title: AI Works For Individuals. Organizations Can't Scale It. - Subtitle: LLMs can do everything. Which is why most organizations can't do anything with them. - Chart Source: Source: Anthropic, March 2026 - Chart Source URL: https://www.anthropic.com/research/labor-market-impacts - Gap Header: Why the gap? - Closer: The gap isn't intelligence. It's infrastructure. #### Chart Legend - Theoretical: Theoretical AI Capability - Actual: Actual Enterprise Adoption #### Gaps ##### Build - Title: Nobody Can Build What They Need - Description: Teams can't turn their specific workflow into a tool. The capability is there. The last mile isn't. ##### Scale - Title: What Works Can't Scale - Description: Every org has power users who've figured it out. That knowledge lives in their heads. No way to share it, templatize it, or hand it off. ##### Shadow - Title: Shadow AI Fills the Vacuum - Description: 40% of orgs have AI subscriptions. 90%+ of employees still use personal accounts. Employees are choosing their own tools. Without infrastructure, adoption goes underground. - Source: Source: Harmonic Security, 2026 ### Traps - Label: Why existing tools fail - Title: Every AI platform forces a tradeoff. AgentShelf doesn't. - Subtitle: Three categories. Three traps. One way out. - Divider: AgentShelf.ai addresses all three — no compromise #### Cards ##### Lock In - Positive: Easy + Powerful - Negative: Not Open - Title: The Lock-In Trap - Players: Anthropic • OpenAI • Microsoft • Salesforce - Description: Enterprise-grade, but you're married to one ecosystem. Switch models? Rebuild everything. ##### Wrapper - Positive: Easy + Open - Negative: Not Powerful - Title: The Wrapper Trap - Players: Lindy • Relevance AI • MindStudio - Description: Easy to start, but built for individuals — not teams. No shared context, no governance, and you'll outgrow them fast. ##### Diy - Positive: Powerful + Open - Negative: Not Easy - Title: The DIY Trap - Players: LangChain • CrewAI • n8n - Description: Maximum power, maximum cost. You'll need a dev team before your first agent ships. #### Solutions ##### Open - Badge: Open - Title: Zero Ecosystem Lock-In - Description: Any model, your API keys, switch providers anytime — OpenAI, Anthropic, Gemini, DeepSeek, and more. ##### Powerful - Badge: Powerful - Title: Real Depth, Not a Wrapper - Description: Agents execute real code in isolated sandboxes. Three-tier shared context across platform, org, and team. ##### Easy - Badge: Easy - Title: Production-Ready Without Engineers - Description: No-code agent builder to production in hours. Multi-agent orchestration built in, not bolted on. #### Bridge - Title: AgentShelf is the layer that makes it work. - Subtitle: Shared context. Any model. Governed by default. ### Usecases - Label: Use cases - Title: Real decisions your team faces every week. - Subtitle: Each one used to take 30 minutes of searching and copy-pasting. Now it's a conversation. #### Cards ##### Knowledge - Category: Knowledge - Title: Tribal knowledge, on demand - Scenario: "What's our process for handling enterprise procurement?" - Flow: Search shared docs → Pull playbook sections → Cite sources → Answer in seconds ##### Sales - Category: Sales - Title: Meeting prep in seconds - Scenario: "I have a call with Acme in 20 minutes." - Flow: Pull account context → Draft talking points → Reference last meeting notes → Share with team ##### Support - Category: Support - Title: Ticket resolution from your docs - Scenario: "Customer says their integration broke after the update." - Flow: Search knowledge base → Match known issue → Draft response → Escalate if needed ### Trust - Label: Enterprise security - Title: Built for the most demanding security teams. - Subtitle: Your agents will pass any security review. Bank-grade encryption, full audit trails, and governance controls built in from day one. #### Cards ##### Keys - Title: Your keys, your data - Description: Bring your own API keys. Your data is never used for model training. AES-256 encryption at rest and in transit — you stay in control. ##### Audit - Title: Complete audit trail - Description: Every agent action, every user interaction, every cost event — logged, timestamped, and attributable. Built for SOC 2, HIPAA, and GDPR requirements. ##### Governance - Title: Governed by default - Description: Role-based access at every level. SSO with Google, Microsoft, GitHub, and SAML. Budget enforcement per user, team, and workspace. #### Compliance ##### Soc2 - Title: SOC 2 Type II - Subtitle: Ready ##### HIPAA - Title: HIPAA - Subtitle: Ready ##### GDPR - Title: GDPR - Subtitle: Compliant ##### Aes256 - Title: AES-256 - Subtitle: Encryption ### FAQ - Title: Questions we get asked a lot. #### Items ##### "We already have ChatGPT / Gemini enterprise licenses." - Answer: Good — that means your team already knows AI works. AgentShelf doesn't replace your LLM. It sits on top and adds what's missing: shared context across agents, team-wide visibility, and the ability to switch models per task. Your reps keep using the best model for each job. Leadership gets the governance layer they need to scale it. ##### "Do I need engineers to use this?" - Answer: No. AgentShelf is built for business teams, not engineering teams. Your ops lead can create an agent, upload your docs, and share it with the team in minutes — no code, no infra, no waiting on a sprint. ##### "We're happy with one LLM provider. Why do we need model optionality?" - Answer: Because these models are leapfrogging each other every quarter. Claude Opus 4.6 leads on heavy reasoning. Gemini 2.5 Flash wins on speed. GPT-4o has strengths neither has matched. Being locked to one provider today means being behind the next time the rankings shift — and they will. Optionality isn't just a cost play. It's a competitive advantage. Your competitors locked to a single vendor will be slower to adopt the next breakthrough. You won't be. ##### "Is my data secure?" - Answer: Yes. AES-256-GCM encryption for all stored data. TLS 1.3 in transit. BYOK support for API keys. SOC 2 Type II-ready controls with full audit logging. Your data is never used for model training. Role-based access control at every level — organization, team, workspace, and agent. ##### "What stops Microsoft or Salesforce from just building this?" - Answer: They already tried — it's called Copilot and Einstein. The problem isn't capability, it's incentive. Their business model depends on keeping you inside their ecosystem. True model agnosticism, bring-your-own-key, and switching between Claude and Gemini per task would cannibalize their own AI revenue. They won't build what undermines their lock-in. We're also solving a different problem. They're building AI on top of their CRM or productivity suite. We're building the infrastructure layer for how teams share, govern, and compound AI across any workflow, any tool, any model. That's not a feature they can bolt on — it's a fundamentally different architecture. The companies that win won't have the best model. They'll be the ones whose institutional knowledge is best organized to use every model. ##### "How long does setup take?" - Answer: Minutes for basic use cases — upload your docs, pick a pre-built agent, and start. For team-wide deployments with custom agents, shared context libraries, and governance policies, plan for a 30-day guided pilot with our team. ### Final CTA - Badge: Early Access Open - Title: Ready to put your team's expertise to work? - Subtitle: Get early access to the platform that turns institutional knowledge into governed AI agents. Limited spots — we onboard hands-on. #### CTA - Primary: Get early access - Secondary: Contact Sales --- ## Discover Agents - Route: https://agentshelf.ai/discover - SEO Title: Discover AI Agents | AgentShelf - SEO Description: Browse and discover AI agents for customer support, CRM, productivity, and more. Find the perfect agent for your workflow. ### Hero - Title: AI That Actually Does the Work - Subtitle: Browse our marketplace of purpose-built agents, and deploy one today. ### Featured - Title: Featured Agents - Badge: Recommended - Subtitle: Get started quickly with these popular, ready-to-use agents ### Categories - Title: Browse by Category - All: All - Productivity: Productivity - Development: Development - Design: Design - Marketing: Marketing - Data Analysis: Data Analysis - Scientific Research: Scientific Research - Customer Support: Customer Support - CRM: CRM - Other: Other ### Filters - Category: Category - All: All Categories #### Search - Placeholder: Search agents... - Label: Search #### Sort - Label: Sort by - Popular: Most Popular - Newest: Newest - Rating: Highest Rated - Name: Name (A-Z) ### Agents - Load More: Load More Agents #### Grid - Showing: Showing {{count}} of {{total}} agents - Page: Page {{current}} of {{total}} #### Card - Learn More: Learn More - View Details: View Details - Request Access: Request Early Access - Featured: Featured - Verified: Verified - Free: Free - Paid: Paid - Freemium: Freemium ### Empty - Title: No agents found - Message: Try adjusting your filters or search terms. ### Error - Title: Unable to load agents - Message: An error occurred while fetching agents. Please try again later. - Retry: Try Again ### Loading - Message: Loading agents... ### CTA - Title: Ready to give your team an unfair advantage? - Subtitle: Join the waitlist to deploy AI agents that actually do the work. - Button: Request Early Access --- ## About - Route: https://agentshelf.ai/about - SEO Title: About Us - AgentShelf.ai - SEO Description: Meet the team behind AgentShelf - experienced enterprise software leaders building the future of AI agent platforms. ### Hero - Lines: Platform Giants Lock You In., GPT Wrappers Cap Your Depth., Dev Frameworks Need Engineers., AgentShelf Doesn't. ### Differentiators - Label: Why we're different - Title: Three categories. Three traps. One way out. - Subtitle: Every alternative forces a tradeoff between Easy, Powerful, and Open. AgentShelf is the first platform that doesn't ask you to. ### Mission - Label: Our story - Title: Why we built AgentShelf - Paragraph1: We built 50+ bespoke AI agents for enterprise clients and saw the same problems: agents trapped in IDEs and CLIs, no way to share them without zipping folders, zero visibility into usage, and non-technical teams locked out entirely. - Paragraph2: The results when agents worked were staggering. Tasks that took weeks now took minutes. But getting them into the hands of the people who needed them most? That was the bottleneck. - Paragraph3: After solving this problem one client at a time, we decided to productize it. AgentShelf is the platform we kept wishing existed: build, manage, and govern AI agents declaratively. No downloads, no coding required. ### Team - Label: Our team - Title: Leadership - Subtitle: Technical depth and GTM. We've built the platforms and sold them inside the teams we're targeting. - Logos Title: Where we've built #### Members ##### Gabe Arce - Role: Chief Executive Officer - Bio: Founded and led two enterprise consultancies (Talavera Solutions, Arce Cloud Consulting). Ex-VP, Axos Bank. 100+ enterprise deployments across regulated industries with a team of 50. - Linkedin: https://www.linkedin.com/in/gaarce/ ##### Edgar Joya - Role: Chief Technology Officer - Bio: Founder (Joya Technology). 7+ years building data engineering & automation systems at Bank of America. VP of Engineering at Talavera Solutions. Shipped production infra across financial services. - Linkedin: https://www.linkedin.com/in/edgarjoya/ ##### Eric Flores - Role: Chief Product Officer - Bio: Founder (consumer data startup, Google for Startups / Manos Accelerator). Founding sales team, Google Cloud LATAM. Shipped voice AI + smart home platforms reaching 10M+ users at Comcast. - Linkedin: https://www.linkedin.com/in/eflo12/ ##### Neil Blackman - Role: Forward Deployed AI Engineer - Bio: Built automation systems across financial services at Axos Bank. Applied AI consulting at Talavera Solutions. Core platform engineer on AgentShelf — built the workspace and the institutional context layer. - Linkedin: https://www.linkedin.com/in/neil-blackman-nnb65a1a/ ### Beliefs - Label: Our principles - Title: What we believe - Subtitle: The non-negotiables behind every product decision we make. #### Items ##### Context That Compounds - Description: Upload your knowledge once. Every agent and every teammate already has it. Context builds over time — it doesn't reset with every conversation. ##### Any Model, No Lock-In - Description: Use the best LLM for each task. Switch providers without rebuilding agents. Your context travels with you, not with a vendor. ##### Governed by Default - Description: RBAC, audit trails, cost controls, and compliance designed in from day one. Not bolted on after the security review kills your rollout. ### CTA - Title: AgentShelf is the layer that makes AI work for teams. - Subtitle: Easy. Powerful. Open. - Primary Button: Request Early Access - Secondary Button: Contact Sales --- ## Work With Us - Route: https://agentshelf.ai/work-with-us - SEO Title: Work With Us - Become a Design Partner - AgentShelf.ai - SEO Description: Join our exclusive design partner program. Get early access to enterprise AI agents, dedicated support, and influence our product roadmap. ### Hero - Title: AI That Actually Does the Work - Subtitle: These agents are live. See what's possible for yours. ### Featured Agents - Badge: Built & Deployed - Title: Featured Agents - Subtitle: Each solves a specific, high-value problem — no code required. - Browse More: Browse more - Tell Us: tell us what you need #### Items ##### OCC Regulatory Scraper - Tagline: Automated compliance monitoring - Benefit Label: For Finserv / Compliance - Benefit Result: Low risk, high reward. Saves hundreds of hours. - Tags: Regulatory, Compliance, Alerts - CTA Label: Request Early Access ##### Salesforce Query Agent - Tagline: Natural language CRM queries - Benefit Label: For Sales Ops - Benefit Result: From "Can someone pull this?" to instant answers. - Tags: Salesforce, CRM, Reporting - CTA Label: Request Early Access ##### Collateral Generation Agent - Tagline: Sales decks and one-pagers, generated - Benefit Label: For Sales / CS Enablement - Benefit Result: Hours of prep work reduced to minutes. - Tags: Decks, One-pagers, CRM - CTA Label: Request Early Access ##### Service Agent (Chat Widget) - Tagline: First line of defense, always on - Benefit Label: For Customer Support - Benefit Result: Deflect 60%+ of repetitive Tier 1 queries. - Tags: Chat, Knowledge Base, Support - CTA Label: Request Early Access ### Timeline - Title: From Intro to Production - Subtitle: A structured engagement where we build together — and you see results before you scale. #### Steps ##### Discovery - Description: We learn your pain points and what success looks like. No pitch — just listening. - Duration: 1 call ##### Data & Demo - Description: You share files and data. We configure the agent and show you it working on your use case. - Duration: 1 week ##### Launch & Fine-tune - Description: Agent runs live with real users. We iterate weekly based on feedback. - Duration: 30-90 days ##### Decision - Description: We review results together. Clear go/no-go — no pressure, no games. - Duration: 1 call ### What We Need #### Need - Title: What We Need From You ##### Items ###### Data access - Description: Files, docs, or system access relevant to your use case ###### A point person - Description: Someone who knows the workflow and can give feedback ###### Time commitment - Description: 1-2 hours/week during pilot for check-ins ###### Clear success criteria - Description: We'll define this together, but you need to know what "good" looks like #### Get - Title: What This Gets You ##### Items ###### See results in weeks, not months - Description: Working agent on your data within 2-3 weeks ###### Design partner pricing - Description: Fraction of the cost of building in-house or hiring consultants ###### No lock-in - Description: Walk away at any point. No long-term contracts until you're ready ###### Production-ready outcome - Description: Real automation that works — not a demo that dies after the call ### CTA - Title: Ready to see what this looks like for your team? - Subtitle: We partner with a handful of companies each quarter. Let's see if there's a fit. - Primary Button: Request Early Access - Secondary Button: Contact Sales --- ## Blog Index - Route: https://agentshelf.ai/blog - SEO Title: Blog | AgentShelf - SEO Description: Insights, product updates, use cases, and company news from AgentShelf. Learn about multi-agent AI, enterprise automation, and best practices. ### Hero - Title: AgentShelf Blog - Subtitle: Insights on enterprise AI, multi-agent systems, and building production-ready AI agents. ### Categories - All: All - Insights: Insights - Product: Product - Use Cases: Use Cases - Company: Company ### Filters - Results Count: {{count}} articles - Results Count Singular: 1 article - No Results: No articles found #### Sort - Label: Sort by - Newest: Newest - Oldest: Oldest - Popular: Most Popular ### Featured - Badge: Featured ### Card - Read Time: {{time}} read - Read More: Read More ### Post #### Breadcrumb - Blog: Blog #### Author - By: By #### Toc - Title: Table of Contents #### Tags - Title: Tags #### Share - Title: Share - Twitter: Share on Twitter - Linkedin: Share on LinkedIn - Copy: Copy Link - Copied: Copied! #### Navigation - Previous: Previous Article - Next: Next Article #### Related - Title: Related Articles - Subtitle: Continue exploring these topics. ### Newsletter - Badge: Stay Updated - Title: Get the Latest on Enterprise AI - Subtitle: Join thousands of AI leaders getting weekly insights on building production-ready AI systems. - Placeholder: Enter your email - CTA: Subscribe - Privacy: We respect your privacy. Unsubscribe at any time. - Success: Thanks for subscribing! - Error: Something went wrong. Please try again. ### Pagination - Previous: Previous - Next: Next - Page: Page {{current}} of {{total}} ### Empty - Title: No Articles Yet - Description: Check back soon for new content. - CTA: View All Articles ### Callout #### Tip - Title: Pro Tip #### Warning - Title: Warning #### Info - Title: Note --- ## Technology - Why Multi-Agent - Route: https://agentshelf.ai/technology/why-multi-agent - SEO Title: Why Multi-Agent Beats the God Agent | AgentShelf - SEO Description: A technical perspective on production AI architecture—why large context windows fail, where tool hallucinations come from, and what actually works in enterprise environments. ### Hero - Badge: Technical Perspective - Title: Why Multi-Agent Beats the "God Agent" - Subtitle: A technical perspective on production AI architecture—why large context windows fail, where tool hallucinations come from, and what actually works in enterprise environments. ### Bottom Line - Label: The Bottom Line - Content: A large context window is a false promise. Even with 200K+ tokens, the model spends compute "finding the needle in the haystack" rather than solving the problem. - Emphasis: We've tried both approaches. Multi-agent wins. ### Failures - Badge: Failure Modes - Title: The God Agent Breaks Down in Three Places #### Cards ##### Context Windows Degrade Fast - Number: 1 - Intro: Even massive context windows degrade. Performance drops well before limits: ###### Items ###### Items Item 1 - Bold: Attention degradation - Text: — critical context gets buried in the middle ###### Items Item 2 - Bold: Instruction following weakens - Text: as context grows ###### Items Item 3 - Bold: Cost scales linearly - Text: — every query pays for the full context, even when 80% is irrelevant ###### Citation - Source: Stanford Research - Text: U-shaped performance curve—accuracy drops 30-50% when relevant info is in the middle vs. beginning/end of context. ##### More Tools = More Hallucinations - Number: 2 - Intro: When an LLM has access to 20+ tools, it improvises when it doesn't know which to use: ###### Items ###### Items Item 1 - Bold: Tool confusion - Text: — calling wrong tools due to overlapping descriptions ###### Items Item 2 - Bold: Parameter hallucination - Text: — inventing plausible but incorrect inputs ###### Items Item 3 - Bold: Cascading errors - Text: — one bad call corrupts downstream reasoning ###### Citation - Source: arXiv Research - Text: Tool selection and usage hallucinations increase substantially as toolsets expand. Pattern consistent with our testing. ##### Determinism Matters in Production - Number: 3 - Intro: Business processes need predictability. God agents introduce variance at every step: ###### Items ###### Items Item 1 - Bold: Different reasoning paths - Text: on identical inputs ###### Items Item 2 - Bold: Non-deterministic tool selection ###### Items Item 3 - Bold: No fallback when it fails - Text: — it's all or nothing ###### Citation - Source: Carnegie Mellon & Gartner - Text: Leading AI agents complete only 30-35% of multi-step tasks reliably. 40% of agentic AI projects will fail by 2027 due to poor reliability. ### Comparison - Badge: Real Example - Title: Same Request, Two Architectures #### Scenario - Label: Customer Service Scenario - Description: "What's my account balance, and can you help me dispute that charge from last Tuesday and also update my email address?" #### God Agent - Title: God Agent Approach - Badges: 20+ tools, 50K+ tokens, All or nothing - Items: Loads all account, billing, support, and profile tools into one context, Hopes model figures out the multi-part request and sequences correctly, If something fails, debug the entire system #### Multi Agent - Title: Multi-Agent Approach - Badges: 3-4 tools each, 5-10K tokens each, Graceful fallback - Items: Router identifies 3 intents, Account Agent handles balance lookup, Dispute Agent handles charge investigation, Profile Agent handles email update ### Payoff - Badge: Operational Payoff - Title: What You Get in Production #### Cards ##### Graceful Degradation - Description: If one agent fails, route to fallback—system stays up ##### Faster Iteration - Description: Update one agent, not the whole system ##### Faster Debugging - Description: Know exactly which agent broke and why ##### Right-Sized Models - Description: Simple queries → Haiku; complex → Opus ##### Audit-Ready - Description: Trace every decision to a specific agent ### Closing - Content: Multi-agent adds coordination overhead—routing, handoffs, state management—but - Emphasis: that complexity is explicit and debuggable - Suffix: , not hidden inside a prompt you can't inspect. ### Sources - Title: Sources #### Items ##### Lost in the Middle - Author: Liu et al. - Source: Stanford/Berkeley, 2024 ##### Reducing Tool Hallucination - Author: Xu et al. - Source: arXiv, 2024 ##### Multi-Agent Framework - Author: Google ##### TheAgentCompany - Author: CMU ##### AI Predictions - Author: Gartner ### CTA - Title: See Our Architecture in Practice - Subtitle: We design multi-agent systems for enterprises in fintech, legal, and compliance-heavy industries. Let's discuss your use case. - Primary: Request Architecture Review - Secondary: View Full Architecture --- ## Technology - Architecture - Route: https://agentshelf.ai/technology/architecture - SEO Title: Multi-Agent Architecture | AgentShelf - Why We Don't Build God Agents - SEO Description: Most AI systems fail because they try to do everything with one monolithic agent. We design specialist agents that collaborate behind a unified experience. ### Hero - Badge: Architecture Philosophy - Title: We Don't Build God Agents - Subtitle: Most AI systems fail because they try to do everything with one monolithic agent. We design specialist agents that collaborate behind a unified experience—so you get reliable outputs even when one agent fails. ### Problems - Badge: The Problem - Title: Why "God Agents" Fail in Production - Subtitle: A monolithic agent handling 15-20+ tools in a massive context window creates predictable failure modes that break enterprise operations. #### Cards ##### Context Degradation - Description: Critical information gets "lost in the middle" of long contexts ##### Tool Confusion - Description: Wrong tool selection when descriptions overlap ##### Parameter Hallucination - Description: Inventing plausible but incorrect inputs ##### Non-Determinism - Description: Unpredictable behavior for financial or regulated operations ##### All-or-Nothing Failure - Description: One error breaks the entire system with no fallback ### Solutions - Badge: Our Approach - Title: Multi-Agent Architecture - Subtitle: Specialized agents with bounded context, right-sized models, and clear responsibilities—while presenting a unified experience to users. #### Cards ##### Agents Stay Focused - Description: Each agent handles 3-4 tools max—so critical info never gets lost in the middle of long contexts. ##### Pay for What You Need - Description: Fast models for simple tasks, advanced models for complex reasoning—so you're not overpaying for every query. ##### System Stays Up - Description: If one agent fails, the rest keep running—so a single error never takes down your whole system. ##### Debug in Minutes - Description: Every decision traced to a specific agent—so you know exactly what happened when something breaks. ### Diagram - Badge: System Design - Title: How It Works - Subtitle: A Router Agent serves as the intelligent front door, classifying user intent and orchestrating responses across specialist agents. #### Layers ##### User - Label: User Interface - Description: "Singular AI" Experience ##### Router - Label: Router Agent - Features: Intent Classification, Multi-Intent Decomposition, Response Orchestration ##### Agents - Label: Specialized Agents - Items: Knowledge Agent, Advisory Agent, Account Agent, Onboarding Agent, Proactive Engine - High Stakes: Transaction Agent ##### Services - Label: Shared Services Layer - Features: Memory & Personalization Store, Audit Trail, User Context Manager ### Tiers - Badge: Model Strategy - Title: Right Model for the Job - Subtitle: We define model tiers based on capability requirements—not vendor lock-in. AgentShelf's LLM Gateway enables automatic failover across 7+ providers. - Headers: Tier, Use Case, Characteristics #### Rows ##### Fast - Badge: fast - Use Case: Classification, retrieval, pattern matching - Characteristics: Low latency (<500ms), minimal reasoning, cost-efficient ##### Balanced - Badge: balanced - Use Case: Conversational guidance, moderate reasoning - Characteristics: Good reasoning capability, balanced cost/performance ##### Advanced - Badge: advanced - Use Case: Complex reasoning, financial calculations, high-stakes - Characteristics: Maximum reasoning, validation logic, confirmation flows ### Experience - Badge: User Experience - Title: One AI, Many Specialists - Subtitle: Users never know there are multiple agents. They experience one unified AI assistant. - Callout: Multi-agent is an implementation detail, not a user experience. #### Cards ##### One Voice - Description: Consistent personality across all agents via shared system prompts ##### One Memory - Description: Shared context store enables continuity across conversations ##### One Conversation - Description: Router maintains thread continuity across all handoffs ##### Seamless Handoffs - Description: No "let me transfer you"—transitions are invisible ### CTA - Title: Ready to See This in Action? - Subtitle: We design multi-agent architectures for enterprises in fintech, legal, and compliance-heavy industries. Let's discuss your use case. - Primary: Request Architecture Review - Secondary: View Infrastructure --- ## Technology - Infrastructure - Route: https://agentshelf.ai/technology/infrastructure - SEO Title: LLM Infrastructure | AgentShelf - Production-Ready in Weeks, Not Years - SEO Description: Seven providers behind one API. Automatic failover. Complete observability. Production-ready in weeks, not years. ### Hero - Badge: Production-Ready Infrastructure - Title: LLM Infrastructure Built for Enterprise - Subtitle: Seven providers behind one API. Automatic failover. Complete observability. Production-ready in weeks, not years. ### Problem - Title: The problem: - Content: Calling an LLM API is easy. Building production infrastructure around it—provider failover, cost tracking, context management, security boundaries—takes - Emphasis: 12-18 months - Suffix: and millions in engineering. ### Architecture - Title: Platform Architecture - Subtitle: A complete stack designed for enterprise AI workloads #### Layers ##### API Gateway - Description: Auth • Rate Limiting • CSRF • Request Tracing ##### Workspace Resolution + Context Assembly ##### LLM Gateway - Description: Circuit Breaker • Auto-Failover • BYOK Support - Providers: Anthropic, OpenAI, Google, xAI, Azure, DeepSeek, AWS Bedrock ##### Telemetry Layer - Description: Per-Request Metrics • Cost Tracking • Usage Records • Audit Logs ### Capabilities - Title: Core Capabilities - Subtitle: Everything you need to run LLMs in production #### Cards ##### LLM Gateway - Description: 7+ providers, one API. Circuit breaker with automatic failover—so agents stay up when OpenAI goes down. - Highlight Value: Up to 90% - Highlight Label: cost savings with intelligent caching ##### Full Observability - Description: Every request captured. Cross-provider analytics in real-time—so you know exactly what failed and how much it cost. - Highlight Value: 7-year - Highlight Label: audit retention for compliance ##### Context Management - Description: Hybrid caching, auto history, PDF/DOCX extraction built-in—so agents remember conversations and process documents automatically. - Highlight Value: Token budget - Highlight Label: tracking per request ##### Enterprise Security - Description: Row-level isolation, AES-256 encryption, full audit trail—so you pass security reviews without custom compliance work. - Highlight Value: SOC 2 ready - Highlight Label: out of the box ### Flywheel - Title: The Intelligence Flywheel - Subtitle: Cross-provider insights that single-vendor platforms can't match #### Steps ##### Every Query ##### Telemetry Captured ##### Cross-Provider Insights #### Detail - Label: Why this matters: - Content: Single-provider platforms only see their own performance. AgentShelf captures cross-provider data—provider, model, tokens, latency, cost. Route simple tasks to fast, cheap models and complex work to advanced ones—then - Emphasis: prove to auditors exactly what happened - Suffix: in any conversation. ### CTA - Title: Skip the 18-Month Build. - Subtitle: Go production-ready in weeks with AgentShelf. - Primary: Request Early Access - Secondary: Contact Sales --- ## Marketplace Catalog - Source: Live marketplace API - API Base: https://api.agentshelf.ai/api - Agent Count: 79 ### Customer Support Tier 1 - Route: https://agentshelf.ai/discover/customer-support-tier1 - Category: customer_support - Featured: Yes - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.8 - Rating Count: 142 - Installs: 0 - Created At: 2025-12-30T18:39:28.846Z - Tags: Customer Support, Chatbot, Helpdesk, Ticketing, 24/7, Automation, Live Chat - Integrations: Zendesk, Intercom, Help Centers Tagline: First line of defense, always on Short Description: Your always-on first line of defense. Answers common questions 24/7 via chat, tickets, and help centers—escalates complex issues to humans. Deploy in hours, scales to any volume. Your always-on first line of defense. Answers common questions 24/7 via chat, tickets, and help centers—escalates complex issues to humans. Deploy in hours, scales to any volume. Perfect For: Support Teams Time Savings: 24/7 instant responses Result: Deploy in hours, scales instantly Traditional: 5-15 min AgentShelf: < 3 seconds Improvement: Instant #### Key Features - 24/7 Chat Support: Greets and assists customers around the clock without delays - Zendesk Integration: Creates and updates tickets, accesses knowledge base - Intercom Connect: Seamless handoff in live chat conversations - Smart Escalation: Routes complex issues to human agents with full context ### Knowledge Base Agent - Route: https://agentshelf.ai/discover/knowledge-base - Category: productivity - Featured: Yes - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.6 - Rating Count: 124 - Installs: 0 - Created At: 2025-12-30T18:39:28.893Z - Tags: Knowledge Management, Documentation, Notion, Confluence, SharePoint, Search, Productivity - Integrations: Notion, Google Drive, Confluence Tagline: Tribal knowledge, on demand Short Description: Search and retrieve information from your knowledge bases, wikis, and documentation instantly. Your always-available expert on internal documentation. Connects to Notion, Drive, and Confluence to surface instant, context-aware answers from docs, policies, and playbooks. New hires ramp faster; everyone stops hunting. Perfect For: Operations Time Savings: New hires productive on day one Result: Instant answers, unified search Traditional: 15-30 min AgentShelf: < 1 second Improvement: 98% #### Key Features - Semantic Search: Understands questions in natural language, not just keywords. - Notion Integration: Searches wikis, databases, and team documentation. - Google Drive Access: Indexes shared docs, sheets, and slides. - Confluence Connect: Pulls from spaces, pages, and embedded files. ### Lead Enrichment Agent - Route: https://agentshelf.ai/discover/lead-enrichment - Category: marketing - Featured: Yes - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.7 - Rating Count: 98 - Installs: 0 - Created At: 2025-12-30T18:39:28.866Z - Tags: Sales, Lead Generation, CRM, Salesforce, HubSpot, LinkedIn, Data Enrichment - Integrations: Salesforce, HubSpot, LinkedIn Tagline: Turn leads into qualified prospects Short Description: Automatically enrich leads with company data, contact information, and social signals from multiple sources. Automates prospect research by gathering intelligence from websites, Google, and other public sources—then delivers actionable insights and outreach tactics. Syncs enriched data directly to Salesforce or HubSpot, eliminating manual entry. Perfect For: Sales Teams Time Savings: 30-60 min → seconds per lead Result: Complete lead profiles, verified data Traditional: 30-60 min AgentShelf: < 5 seconds Improvement: 95% #### Key Features - Website Scraping: Extracts key info from prospect company websites - SharePoint Integration: Access internal docs and company knowledge - Intent analysis: Digests findings into actionable recommendations - CRM Auto-Sync: Automatically updates Salesforce or HubSpot with enriched data and notes ### Meeting Prep Agent - Route: https://agentshelf.ai/discover/meeting-prep - Category: productivity - Featured: Yes - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.9 - Rating Count: 87 - Installs: 0 - Created At: 2025-12-30T18:39:28.879Z - Tags: Productivity, Meetings, Google Workspace, Microsoft 365, Slack, Notion, Time Management - Integrations: Salesforce, SharePoint, OneDrive Tagline: Every rep walks in prepared Short Description: Prepare for meetings instantly by gathering context, summarizing documents, and generating talking points. Creates comprehensive meeting prep briefs by pulling CRM data, account history, and internal resources—then synthesizes everything into one actionable document, generated minutes before the meeting. Perfect For: Sales Teams Time Savings: Hours of prep → generated instantly Result: Complete prep, confident meetings Traditional: 1-2 hours AgentShelf: < 2 minutes Improvement: 97% #### Key Features - CRM Data Pull: Extracts account history, contacts, and deal stage from Salesforce - SharePoint Integration: Accesses sales playbooks, battle cards, and enablement docs - OneDrive Sync: Pulls proposals, decks, and shared collateral from OneDrive - Prep Summary Generation: Creates briefing docs with talking points and action items ### AlphaFold Protein Structure - Route: https://agentshelf.ai/discover/alphafold-protein - Category: scientific_research - Featured: No - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.9 - Rating Count: 42 - Installs: 0 - Created At: 2025-12-30T18:39:28.974Z - Tags: UniProt, AlphaFold, Drug Discovery, Structural Biology, Proteins, Research Tagline: Protein insights at your fingertips Short Description: Analyze protein structures and predict molecular interactions using AlphaFold data. Access AlphaFold protein structure predictions and analyze molecular interactions. Accelerate drug discovery and structural biology research. Perfect For: Researchers Time Savings: Weeks of research → Days Result: Accurate structure predictions Traditional: Weeks AgentShelf: Minutes Improvement: 99% #### Key Features - Structure Lookup: Search AlphaFold database by UniProt ID - Interaction Analysis: Predict protein-protein interactions - 3D Visualization: View protein structures in 3D - Export Data: Export structures for further analysis ### AlphaFold Protein Structure Agent - Route: https://agentshelf.ai/discover/alphafold-protein-structure-agent - Category: scientific_research - Featured: No - Pricing: Freemium - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.9 - Rating Count: 43 - Installs: 0 - Created At: 2025-12-06T01:03:45.033Z Tagline: Access 200M+ AI-predicted protein structures for structural biology research. Short Description: Access 200M+ AI-predicted protein structures for structural biology research. Access 200M+ AI-predicted protein structures for structural biology research. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Apollo.io Enrichment Agent - Route: https://agentshelf.ai/discover/apollo-enrichment - Category: crm - Featured: No - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.6 - Rating Count: 108 - Installs: 0 - Created At: 2025-12-30T18:39:28.986Z - Tags: Apollo.io, Contacts, B2B, Enrichment, Sales, CRM Tagline: B2B data enrichment, automated Short Description: Enrich contact and company data using Apollo.io's database of B2B contacts. Automatically enrich your CRM contacts with Apollo.io data. Get verified emails, phone numbers, company info, and buying signals. Perfect For: Sales Teams Time Savings: Manual research → Instant enrichment Result: Complete, verified contact data Traditional: 15-30 min AgentShelf: < 5 seconds Improvement: 98% #### Key Features - Contact Enrichment: Get verified emails and phone numbers - Company Data: Access company size, revenue, and tech stack - Buying Signals: Identify prospects ready to buy - CRM Sync: Auto-update Salesforce or HubSpot ### Apollo.io Enrichment Agent - Route: https://agentshelf.ai/discover/apolloio-enrichment-agent - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: John Smith - Publisher Verified: No - Rating: 4.7 - Rating Count: 54 - Installs: 0 - Created At: 2025-12-08T19:08:40.057Z - Tags: Apollo.io, Contacts, B2B, Enrichment, Sales, CRM Tagline: B2B data enrichment, automated Short Description: B2B contact discovery and company enrichment via Apollo.io API with email verification. Automatically enrich your CRM contacts with Apollo.io data. Get verified emails, phone numbers, company info, and buying signals. Perfect For: Sales Teams Time Savings: Manual research → Instant enrichment Result: Complete, verified contact data Traditional: 15-30 min AgentShelf: < 5 seconds Improvement: 98% #### Key Features - Contact Enrichment: Get verified emails and phone numbers - Company Data: Access company size, revenue, and tech stack - Buying Signals: Identify prospects ready to buy - CRM Sync: Auto-update Salesforce or HubSpot ### Artifact Builder - Route: https://agentshelf.ai/discover/artifact-builder - Category: development - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.7 - Rating Count: 78 - Installs: 0 - Created At: 2025-12-06T01:03:44.363Z Tagline: Build multi-component Claude artifacts with React, Tailwind, and shadcn/ui. Short Description: Build multi-component Claude artifacts with React, Tailwind, and shadcn/ui. Build multi-component Claude artifacts with React, Tailwind, and shadcn/ui. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Batch Enrichment Agent - Route: https://agentshelf.ai/discover/batch-enrichment-agent - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 35 - Installs: 0 - Created At: 2025-12-08T19:08:40.573Z Tagline: Orchestrate batch enrichment operations with rate limiting, progress tracking, and checkpoint/resume. Short Description: Orchestrate batch enrichment operations with rate limiting, progress tracking, and checkpoint/resume. Orchestrate batch enrichment operations with rate limiting, progress tracking, and checkpoint/resume. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### bioRxiv Preprint Agent - Route: https://agentshelf.ai/discover/biorxiv-preprint-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 31 - Installs: 0 - Created At: 2025-12-06T01:03:45.168Z Tagline: Search and download life sciences preprints from bioRxiv by keyword or author. Short Description: Search and download life sciences preprints from bioRxiv by keyword or author. Search and download life sciences preprints from bioRxiv by keyword or author. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Brand Guidelines Manager - Route: https://agentshelf.ai/discover/brand-guidelines - Category: marketing - Featured: No - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.4 - Rating Count: 56 - Installs: 0 - Created At: 2025-12-30T18:39:29.016Z - Tags: Brand, Identity, Marketing, Style Guide, Consistency, Content Tagline: Brand consistency, guaranteed Short Description: Maintain brand consistency by checking content against your style guide and brand rules. Ensure every piece of content matches your brand guidelines. Check colors, fonts, tone of voice, and messaging for consistency. Perfect For: Marketing Teams Time Savings: Manual review → Automated checks Result: On-brand content, every time Traditional: 1-2 hours AgentShelf: 5 minutes Improvement: 90% #### Key Features - Style Guide Check: Verify content against brand guidelines - Tone Analysis: Ensure consistent tone of voice - Color Validation: Check color usage against palette - Asset Library: Access approved brand assets ### Brand Guidelines Manager - Route: https://agentshelf.ai/discover/brand-guidelines-manager - Category: marketing - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.6 - Rating Count: 87 - Installs: 0 - Created At: 2025-12-06T01:03:44.489Z - Tags: Brand, Identity, Marketing, Style Guide, Consistency, Content Tagline: Brand consistency, guaranteed Short Description: Apply and manage brand colors, typography, and visual identity consistently. Ensure every piece of content matches your brand guidelines. Check colors, fonts, tone of voice, and messaging for consistency. Perfect For: Marketing Teams Time Savings: Manual review → Automated checks Result: On-brand content, every time Traditional: 1-2 hours AgentShelf: 5 minutes Improvement: 90% #### Key Features - Style Guide Check: Verify content against brand guidelines - Tone Analysis: Ensure consistent tone of voice - Color Validation: Check color usage against palette - Asset Library: Access approved brand assets ### Browser Automation Engineer - Route: https://agentshelf.ai/discover/browser-automation - Category: development - Featured: No - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.5 - Rating Count: 72 - Installs: 0 - Created At: 2025-12-30T18:39:29.001Z - Tags: Browser, Playwright, E2E, Testing, Automation, QA Tagline: Browser testing, automated Short Description: Automate browser testing with Playwright for E2E testing and web automation. Create robust browser automation scripts using Playwright. Write E2E tests, scrape websites, and automate repetitive web tasks. Perfect For: Developers Time Savings: Manual testing → Automated E2E Result: Reliable, maintainable tests Traditional: 2-4 hours AgentShelf: 30 minutes Improvement: 85% #### Key Features - E2E Testing: Write comprehensive end-to-end tests - Web Scraping: Extract data from any website - Task Automation: Automate repetitive browser tasks - Cross-browser: Test on Chrome, Firefox, Safari ### Browser Automation Engineer - Route: https://agentshelf.ai/discover/browser-automation-engineer - Category: development - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.7 - Rating Count: 132 - Installs: 0 - Created At: 2025-12-06T01:03:43.803Z - Tags: Browser, Playwright, E2E, Testing, Automation, QA Tagline: Browser testing, automated Short Description: Automate browser testing with Playwright for E2E tests and web scraping. Create robust browser automation scripts using Playwright. Write E2E tests, scrape websites, and automate repetitive web tasks. Perfect For: Developers Time Savings: Manual testing → Automated E2E Result: Reliable, maintainable tests Traditional: 2-4 hours AgentShelf: 30 minutes Improvement: 85% #### Key Features - E2E Testing: Write comprehensive end-to-end tests - Web Scraping: Extract data from any website - Task Automation: Automate repetitive browser tasks - Cross-browser: Test on Chrome, Firefox, Safari ### Canvas Designer - Route: https://agentshelf.ai/discover/canvas-designer - Category: design - Featured: No - Pricing: Freemium - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.6 - Rating Count: 124 - Installs: 0 - Created At: 2025-12-06T01:03:42.558Z Tagline: Create museum-quality visual art and designs in PDF and PNG formats. Short Description: Create museum-quality visual art and designs in PDF and PNG formats. Create museum-quality visual art and designs in PDF and PNG formats. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### ChEMBL Drug Discovery Agent - Route: https://agentshelf.ai/discover/chembl-drug-discovery-agent - Category: scientific_research - Featured: No - Pricing: Freemium - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 28 - Installs: 0 - Created At: 2025-12-06T01:03:45.283Z Tagline: Query 2M+ bioactive molecules and 19M+ bioactivity measurements for drug discovery. Short Description: Query 2M+ bioactive molecules and 19M+ bioactivity measurements for drug discovery. Query 2M+ bioactive molecules and 19M+ bioactivity measurements for drug discovery. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Classification Agent - Route: https://agentshelf.ai/discover/classification-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 31 - Installs: 0 - Created At: 2025-12-08T19:08:41.363Z Tagline: Classify content into categories using LLM for intent detection and entity typing. Short Description: Classify content into categories using LLM for intent detection and entity typing. Classify content into categories using LLM for intent detection and entity typing. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### ClinicalTrials.gov Agent - Route: https://agentshelf.ai/discover/clinicaltrialsgov-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.8 - Rating Count: 39 - Installs: 0 - Created At: 2025-12-06T01:03:45.402Z Tagline: Search clinical trials by condition, drug, location, or phase for research and patient matching. Short Description: Search clinical trials by condition, drug, location, or phase for research and patient matching. Search clinical trials by condition, drug, location, or phase for research and patient matching. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### ClinPGx Pharmacogenomics Agent - Route: https://agentshelf.ai/discover/clinpgx-pharmacogenomics-agent - Category: scientific_research - Featured: No - Pricing: Freemium - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.9 - Rating Count: 18 - Installs: 0 - Created At: 2025-12-06T01:03:45.521Z Tagline: Access gene-drug interactions and CPIC guidelines for precision medicine decisions. Short Description: Access gene-drug interactions and CPIC guidelines for precision medicine decisions. Access gene-drug interactions and CPIC guidelines for precision medicine decisions. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Co-Investor Discovery Agent - Route: https://agentshelf.ai/discover/co-investor-discovery-agent - Category: data_analysis - Featured: No - Pricing: Paid - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 23 - Installs: 0 - Created At: 2025-12-08T19:08:41.209Z Tagline: Identify co-investment patterns among VC/PE firms and build investor relationship networks. Short Description: Identify co-investment patterns among VC/PE firms and build investor relationship networks. Identify co-investment patterns among VC/PE firms and build investor relationship networks. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Content Extractor Agent - Route: https://agentshelf.ai/discover/content-extractor-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.6 - Rating Count: 31 - Installs: 0 - Created At: 2025-12-08T19:08:40.972Z Tagline: Extract structured data from HTML including tables, contact info, prices, and dates. Short Description: Extract structured data from HTML including tables, contact info, prices, and dates. Extract structured data from HTML including tables, contact info, prices, and dates. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Context Analyzer Agent - Route: https://agentshelf.ai/discover/context-analyzer-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 25 - Installs: 0 - Created At: 2025-12-08T19:08:41.294Z Tagline: Analyze context relevance and quality before LLM operations to optimize token usage. Short Description: Analyze context relevance and quality before LLM operations to optimize token usage. Analyze context relevance and quality before LLM operations to optimize token usage. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Conversation Manager Agent - Route: https://agentshelf.ai/discover/conversation-manager-agent - Category: development - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.7 - Rating Count: 27 - Installs: 0 - Created At: 2025-12-08T19:08:41.805Z Tagline: Manage multi-turn conversations with session state, context windowing, and checkpoints. Short Description: Manage multi-turn conversations with session state, context windowing, and checkpoints. Manage multi-turn conversations with session state, context windowing, and checkpoints. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Crunchbase API Agent - Route: https://agentshelf.ai/discover/crunchbase-api-agent - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.6 - Rating Count: 45 - Installs: 0 - Created At: 2025-12-08T19:08:40.172Z Tagline: Retrieve company profiles, funding rounds, and investor data from Crunchbase API. Short Description: Retrieve company profiles, funding rounds, and investor data from Crunchbase API. Retrieve company profiles, funding rounds, and investor data from Crunchbase API. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Crunchbase Web Scraper - Route: https://agentshelf.ai/discover/crunchbase-web-scraper - Category: data_analysis - Featured: No - Pricing: Paid - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.5 - Rating Count: 33 - Installs: 0 - Created At: 2025-12-08T19:08:40.816Z Tagline: Extract company, funding, and investor data from Crunchbase as fallback to API access. Short Description: Extract company, funding, and investor data from Crunchbase as fallback to API access. Extract company, funding, and investor data from Crunchbase as fallback to API access. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Data Extraction Agent - Route: https://agentshelf.ai/discover/data-extraction-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.9 - Rating Count: 36 - Installs: 0 - Created At: 2025-12-08T19:08:41.462Z Tagline: Extract structured data from unstructured text with schema validation and confidence scoring. Short Description: Extract structured data from unstructured text with schema validation and confidence scoring. Extract structured data from unstructured text with schema validation and confidence scoring. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Data Validator Agent - Route: https://agentshelf.ai/discover/data-validator-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 42 - Installs: 0 - Created At: 2025-12-08T19:08:40.262Z Tagline: Validate and standardize data quality with format checks and quality scoring. Short Description: Validate and standardize data quality with format checks and quality scoring. Validate and standardize data quality with format checks and quality scoring. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Data Visualization Specialist - Route: https://agentshelf.ai/discover/data-visualization - Category: data_analysis - Featured: No - Pricing: Free - Publisher: AgentShelf Team - Publisher Verified: Yes - Rating: 4.7 - Rating Count: 64 - Installs: 0 - Created At: 2025-12-30T18:39:28.962Z - Tags: Data Visualization, D3.js, SVG, Interactive, Charts, Dashboards Tagline: Data stories that captivate Short Description: Create interactive data visualizations with D3.js charts and network graphs. Transform your data into stunning visualizations. Create interactive charts, network graphs, dashboards, and infographics that tell compelling stories. Perfect For: Data Teams Time Savings: Days of design → Hours Result: Interactive, publication-ready visuals Traditional: 2-3 days AgentShelf: 2 hours Improvement: 90% #### Key Features - Interactive Charts: Build D3.js and Chart.js visualizations - Network Graphs: Visualize relationships and connections - Dashboards: Create comprehensive data dashboards - Export Options: Export to SVG, PNG, or embed code ### Data Visualization Specialist - Route: https://agentshelf.ai/discover/data-visualization-specialist - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 178 - Installs: 0 - Created At: 2025-12-06T01:03:43.361Z - Tags: Data Visualization, D3.js, SVG, Interactive, Charts, Dashboards Tagline: Data stories that captivate Short Description: Create interactive data visualizations with D3.js charts and network diagrams. Transform your data into stunning visualizations. Create interactive charts, network graphs, dashboards, and infographics that tell compelling stories. Perfect For: Data Teams Time Savings: Days of design → Hours Result: Interactive, publication-ready visuals Traditional: 2-3 days AgentShelf: 2 hours Improvement: 90% #### Key Features - Interactive Charts: Build D3.js and Chart.js visualizations - Network Graphs: Visualize relationships and connections - Dashboards: Create comprehensive data dashboards - Export Options: Export to SVG, PNG, or embed code ### Deduplication Agent - Route: https://agentshelf.ai/discover/deduplication-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 38 - Installs: 0 - Created At: 2025-12-08T19:08:40.337Z Tagline: Identify and manage duplicate records using email, LinkedIn, phone, and fuzzy name matching. Short Description: Identify and manage duplicate records using email, LinkedIn, phone, and fuzzy name matching. Identify and manage duplicate records using email, LinkedIn, phone, and fuzzy name matching. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Document Specialist - Route: https://agentshelf.ai/discover/document-specialist - Category: productivity - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: Yes - Rating: 4.6 - Rating Count: 82 - Installs: 0 - Created At: 2025-12-06T01:03:41.790Z - Tags: DOCX, Word, Editing, Professional, Templates, Writing Tagline: Professional documents, effortlessly Short Description: Create, edit, and analyze Word documents with tracked changes and formatting. Handle all your Word document needs. Create professional documents, edit with tracked changes, apply consistent formatting, and analyze document content. Perfect For: Content Teams Time Savings: Hours of editing → Minutes Result: Professional docs, every time Traditional: 1-2 hours AgentShelf: 15 minutes Improvement: 85% #### Key Features - Document Creation: Generate documents from templates - Track Changes: Edit with full revision history - Formatting: Apply consistent professional styling - Content Analysis: Analyze and summarize documents ### Enrichment Pipeline Agent - Route: https://agentshelf.ai/discover/enrichment-pipeline-agent - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.9 - Rating Count: 41 - Installs: 0 - Created At: 2025-12-08T19:08:40.642Z Tagline: Orchestrate complete enrichment workflows coordinating query, validation, enrichment, and CRM updates. Short Description: Orchestrate complete enrichment workflows coordinating query, validation, enrichment, and CRM updates. Orchestrate complete enrichment workflows coordinating query, validation, enrichment, and CRM updates. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Field Mapper Agent - Route: https://agentshelf.ai/discover/field-mapper-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.6 - Rating Count: 31 - Installs: 0 - Created At: 2025-12-08T19:08:40.405Z Tagline: Map fields between external data sources and Salesforce with transformation rules. Short Description: Map fields between external data sources and Salesforce with transformation rules. Map fields between external data sources and Salesforce with transformation rules. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Generative Artist - Route: https://agentshelf.ai/discover/generative-artist - Category: design - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.5 - Rating Count: 89 - Installs: 0 - Created At: 2025-12-06T01:03:43.203Z Tagline: Create algorithmic art using p5.js with flow fields and particle systems. Short Description: Create algorithmic art using p5.js with flow fields and particle systems. Create algorithmic art using p5.js with flow fields and particle systems. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### GEO Gene Expression Agent - Route: https://agentshelf.ai/discover/geo-gene-expression-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 34 - Installs: 0 - Created At: 2025-12-06T01:03:45.631Z Tagline: Search and download gene expression datasets from NCBI GEO for transcriptomics. Short Description: Search and download gene expression datasets from NCBI GEO for transcriptomics. Search and download gene expression datasets from NCBI GEO for transcriptomics. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### GIF Animator - Route: https://agentshelf.ai/discover/gif-animator - Category: design - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.8 - Rating Count: 167 - Installs: 0 - Created At: 2025-12-06T01:03:43.043Z Tagline: Create optimized animated GIFs for Slack and social media platforms. Short Description: Create optimized animated GIFs for Slack and social media platforms. Create optimized animated GIFs for Slack and social media platforms. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### GWAS Catalog Agent - Route: https://agentshelf.ai/discover/gwas-catalog-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 24 - Installs: 0 - Created At: 2025-12-06T01:03:45.762Z Tagline: Query SNP-trait associations for genetic epidemiology and polygenic risk studies. Short Description: Query SNP-trait associations for genetic epidemiology and polygenic risk studies. Query SNP-trait associations for genetic epidemiology and polygenic risk studies. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### HMDB Metabolome Agent - Route: https://agentshelf.ai/discover/hmdb-metabolome-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.6 - Rating Count: 21 - Installs: 0 - Created At: 2025-12-06T01:03:45.875Z Tagline: Access 220K+ human metabolites with chemical properties and biomarker data. Short Description: Access 220K+ human metabolites with chemical properties and biomarker data. Access 220K+ human metabolites with chemical properties and biomarker data. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Internal Communications Specialist - Route: https://agentshelf.ai/discover/internal-communications-specialist - Category: marketing - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 112 - Installs: 0 - Created At: 2025-12-06T01:03:44.649Z Tagline: Create effective internal communications using professional templates and formats. Short Description: Create effective internal communications using professional templates and formats. Create effective internal communications using professional templates and formats. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### iOS Test Automation Engineer - Route: https://agentshelf.ai/discover/ios-test-automation-engineer - Category: development - Featured: No - Pricing: Freemium - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.9 - Rating Count: 67 - Installs: 0 - Created At: 2025-12-06T01:03:44.102Z Tagline: Comprehensive iOS testing with 21 production scripts for UI and accessibility. Short Description: Comprehensive iOS testing with 21 production scripts for UI and accessibility. Comprehensive iOS testing with 21 production scripts for UI and accessibility. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### KEGG Pathway Agent - Route: https://agentshelf.ai/discover/kegg-pathway-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.7 - Rating Count: 33 - Installs: 0 - Created At: 2025-12-06T01:03:45.981Z Tagline: Analyze biological pathways and gene-pathway mappings across organisms. Short Description: Analyze biological pathways and gene-pathway mappings across organisms. Analyze biological pathways and gene-pathway mappings across organisms. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### LinkedIn Profile Scraper - Route: https://agentshelf.ai/discover/linkedin-profile-scraper - Category: data_analysis - Featured: No - Pricing: Paid - Publisher: John Smith - Publisher Verified: No - Rating: 4.6 - Rating Count: 52 - Installs: 0 - Created At: 2025-12-08T19:08:40.724Z Tagline: Extract profile and company data from LinkedIn with rate limiting and anti-detection measures. Short Description: Extract profile and company data from LinkedIn with rate limiting and anti-detection measures. Extract profile and company data from LinkedIn with rate limiting and anti-detection measures. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### MCP Server Builder - Route: https://agentshelf.ai/discover/mcp-server-builder - Category: development - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.9 - Rating Count: 95 - Installs: 0 - Created At: 2025-12-06T01:03:43.671Z Tagline: Build Model Context Protocol servers for LLM-external service integration. Short Description: Build Model Context Protocol servers for LLM-external service integration. Build Model Context Protocol servers for LLM-external service integration. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Merge Resolution Agent - Route: https://agentshelf.ai/discover/merge-resolution-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.5 - Rating Count: 24 - Installs: 0 - Created At: 2025-12-08T19:08:40.501Z Tagline: Resolve data conflicts from multiple sources using priority, recency, and completeness strategies. Short Description: Resolve data conflicts from multiple sources using priority, recency, and completeness strategies. Resolve data conflicts from multiple sources using priority, recency, and completeness strategies. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Metabolomics Workbench Agent - Route: https://agentshelf.ai/discover/metabolomics-workbench-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.6 - Rating Count: 14 - Installs: 0 - Created At: 2025-12-06T01:03:46.102Z Tagline: Access 4,200+ metabolomics studies with RefMet nomenclature and m/z searches. Short Description: Access 4,200+ metabolomics studies with RefMet nomenclature and m/z searches. Access 4,200+ metabolomics studies with RefMet nomenclature and m/z searches. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### News Aggregator Agent - Route: https://agentshelf.ai/discover/news-aggregator-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.5 - Rating Count: 28 - Installs: 0 - Created At: 2025-12-08T19:08:41.044Z Tagline: Collect and aggregate news articles about companies and people from multiple sources. Short Description: Collect and aggregate news articles about companies and people from multiple sources. Collect and aggregate news articles about companies and people from multiple sources. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Open Targets Drug Discovery Agent - Route: https://agentshelf.ai/discover/open-targets-drug-discovery-agent - Category: scientific_research - Featured: No - Pricing: Freemium - Publisher: John Smith - Publisher Verified: No - Rating: 4.9 - Rating Count: 27 - Installs: 0 - Created At: 2025-12-06T01:03:46.205Z Tagline: Identify therapeutic targets with disease associations, tractability, and safety data. Short Description: Identify therapeutic targets with disease associations, tractability, and safety data. Identify therapeutic targets with disease associations, tractability, and safety data. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### PDB Protein Structure Agent - Route: https://agentshelf.ai/discover/pdb-protein-structure-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.8 - Rating Count: 47 - Installs: 0 - Created At: 2025-12-06T01:03:46.299Z Tagline: Search and download 200,000+ experimental 3D protein structures from RCSB PDB. Short Description: Search and download 200,000+ experimental 3D protein structures from RCSB PDB. Search and download 200,000+ experimental 3D protein structures from RCSB PDB. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### PDF Specialist - Route: https://agentshelf.ai/discover/pdf-specialist - Category: productivity - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: Yes - Rating: 4.4 - Rating Count: 78 - Installs: 0 - Created At: 2025-12-06T01:03:42.028Z - Tags: PDF, Documents, Analysis, Forms, Extraction Tagline: Master your PDF workflows Short Description: Extract, create, merge, split, and fill PDF documents with precision. Handle all your PDF needs in one place. Extract text and data, create new PDFs, merge multiple files, split documents, and fill out forms automatically. Perfect For: Office Teams Time Savings: Manual PDF work → Automated Result: Process PDFs in seconds Traditional: 30-60 min AgentShelf: 2 minutes Improvement: 95% #### Key Features - Text Extraction: Extract text and data from any PDF - Merge & Split: Combine or separate PDF documents - Form Filling: Automatically fill PDF forms - PDF Creation: Generate PDFs from templates ### Presentation Builder - Route: https://agentshelf.ai/discover/presentation-builder - Category: productivity - Featured: No - Pricing: Freemium - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.7 - Rating Count: 156 - Installs: 0 - Created At: 2025-12-06T01:03:42.217Z Tagline: Create stunning PowerPoint presentations with professional layouts and design. Short Description: Create stunning PowerPoint presentations with professional layouts and design. Create stunning PowerPoint presentations with professional layouts and design. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Prompt Builder Agent - Route: https://agentshelf.ai/discover/prompt-builder-agent - Category: development - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.7 - Rating Count: 29 - Installs: 0 - Created At: 2025-12-08T19:08:41.535Z Tagline: Construct optimized prompts for LLM interactions with templates and token management. Short Description: Construct optimized prompts for LLM interactions with templates and token management. Construct optimized prompts for LLM interactions with templates and token management. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### PubChem Chemistry Agent - Route: https://agentshelf.ai/discover/pubchem-chemistry-agent - Category: scientific_research - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 41 - Installs: 0 - Created At: 2025-12-06T01:03:46.482Z Tagline: Search 110M+ compounds for chemical properties, similarity, and bioactivity data. Short Description: Search 110M+ compounds for chemical properties, similarity, and bioactivity data. Search 110M+ compounds for chemical properties, similarity, and bioactivity data. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Response Parser Agent - Route: https://agentshelf.ai/discover/response-parser-agent - Category: development - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.6 - Rating Count: 24 - Installs: 0 - Created At: 2025-12-08T19:08:41.696Z Tagline: Parse and validate LLM responses with error recovery and quality scoring. Short Description: Parse and validate LLM responses with error recovery and quality scoring. Parse and validate LLM responses with error recovery and quality scoring. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Apex Developer Agent - Route: https://agentshelf.ai/discover/salesforce-apex-developer-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.9 - Rating Count: 58 - Installs: 0 - Created At: 2025-12-08T19:08:42.268Z Tagline: Create production-ready Apex classes with bulkification, security, and error handling. Short Description: Create production-ready Apex classes with bulkification, security, and error handling. Create production-ready Apex classes with bulkification, security, and error handling. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Bulk Data Agent - Route: https://agentshelf.ai/discover/salesforce-bulk-data-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.7 - Rating Count: 36 - Installs: 0 - Created At: 2025-12-08T19:08:43.162Z Tagline: Handle bulk data operations with transformation, validation, and error handling. Short Description: Handle bulk data operations with transformation, validation, and error handling. Handle bulk data operations with transformation, validation, and error handling. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Code Review Agent - Route: https://agentshelf.ai/discover/salesforce-code-review-agent - Category: crm - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 39 - Installs: 0 - Created At: 2025-12-08T19:08:42.946Z Tagline: Review Apex code against best practices for bulkification, security, and governor limits. Short Description: Review Apex code against best practices for bulkification, security, and governor limits. Review Apex code against best practices for bulkification, security, and governor limits. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Custom Object Agent - Route: https://agentshelf.ai/discover/salesforce-custom-object-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.8 - Rating Count: 45 - Installs: 0 - Created At: 2025-12-08T19:08:42.069Z Tagline: Design and configure custom objects, fields, and relationships following data modeling best practices. Short Description: Design and configure custom objects, fields, and relationships following data modeling best practices. Design and configure custom objects, fields, and relationships following data modeling best practices. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Deployment Agent - Route: https://agentshelf.ai/discover/salesforce-deployment-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.7 - Rating Count: 41 - Installs: 0 - Created At: 2025-12-08T19:08:43.051Z Tagline: Manage metadata deployments with validation, dependency checking, and rollback support. Short Description: Manage metadata deployments with validation, dependency checking, and rollback support. Manage metadata deployments with validation, dependency checking, and rollback support. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Flow Builder Agent - Route: https://agentshelf.ai/discover/salesforce-flow-builder-agent - Category: crm - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.9 - Rating Count: 51 - Installs: 0 - Created At: 2025-12-08T19:08:42.153Z Tagline: Create declarative Salesforce Flows with bulkification, error handling, and governor limit awareness. Short Description: Create declarative Salesforce Flows with bulkification, error handling, and governor limit awareness. Create declarative Salesforce Flows with bulkification, error handling, and governor limit awareness. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Integration Agent - Route: https://agentshelf.ai/discover/salesforce-integration-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.8 - Rating Count: 40 - Installs: 0 - Created At: 2025-12-08T19:08:42.658Z Tagline: Create secure REST/SOAP integrations with retry logic and Named Credentials. Short Description: Create secure REST/SOAP integrations with retry logic and Named Credentials. Create secure REST/SOAP integrations with retry logic and Named Credentials. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce LWC Developer Agent - Route: https://agentshelf.ai/discover/salesforce-lwc-developer-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 47 - Installs: 0 - Created At: 2025-12-08T19:08:42.363Z Tagline: Build accessible Lightning Web Components with LDS integration and Jest testing. Short Description: Build accessible Lightning Web Components with LDS integration and Jest testing. Build accessible Lightning Web Components with LDS integration and Jest testing. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Orchestrator Agent - Route: https://agentshelf.ai/discover/salesforce-orchestrator-agent - Category: crm - Featured: No - Pricing: Freemium - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.9 - Rating Count: 23 - Installs: 0 - Created At: 2025-12-08T19:08:43.482Z Tagline: Coordinate multiple Salesforce agents in workflows with sequencing and progress tracking. Short Description: Coordinate multiple Salesforce agents in workflows with sequencing and progress tracking. Coordinate multiple Salesforce agents in workflows with sequencing and progress tracking. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce PersonAccount Agent - Route: https://agentshelf.ai/discover/salesforce-personaccount-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.8 - Rating Count: 31 - Installs: 0 - Created At: 2025-12-08T19:08:43.285Z Tagline: Manage Person Account records with enrichment, validation, and bulk operations. Short Description: Manage Person Account records with enrichment, validation, and bulk operations. Manage Person Account records with enrichment, validation, and bulk operations. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Planning Agent - Route: https://agentshelf.ai/discover/salesforce-planning-agent - Category: crm - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.7 - Rating Count: 25 - Installs: 0 - Created At: 2025-12-08T19:08:43.391Z Tagline: Analyze requirements and create detailed implementation plans with task sequencing. Short Description: Analyze requirements and create detailed implementation plans with task sequencing. Analyze requirements and create detailed implementation plans with task sequencing. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Security Review Agent - Route: https://agentshelf.ai/discover/salesforce-security-review-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.9 - Rating Count: 34 - Installs: 0 - Created At: 2025-12-08T19:08:42.849Z Tagline: Scan code for CRUD/FLS violations, XSS, SOQL injection, and security vulnerabilities. Short Description: Scan code for CRUD/FLS violations, XSS, SOQL injection, and security vulnerabilities. Scan code for CRUD/FLS violations, XSS, SOQL injection, and security vulnerabilities. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce SOQL Agent - Route: https://agentshelf.ai/discover/salesforce-soql-agent - Category: crm - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.9 - Rating Count: 55 - Installs: 0 - Created At: 2025-12-08T19:08:42.563Z Tagline: Create optimized, secure SOQL queries that leverage indexes and respect governor limits. Short Description: Create optimized, secure SOQL queries that leverage indexes and respect governor limits. Create optimized, secure SOQL queries that leverage indexes and respect governor limits. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Test Class Agent - Route: https://agentshelf.ai/discover/salesforce-test-class-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 45 - Installs: 0 - Created At: 2025-12-08T19:08:42.761Z Tagline: Create comprehensive test classes with high code coverage and bulk testing. Short Description: Create comprehensive test classes with high code coverage and bulk testing. Create comprehensive test classes with high code coverage and bulk testing. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Salesforce Trigger Agent - Route: https://agentshelf.ai/discover/salesforce-trigger-agent - Category: crm - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.7 - Rating Count: 43 - Installs: 0 - Created At: 2025-12-08T19:08:42.461Z Tagline: Create bulkified triggers with handler patterns that prevent recursion. Short Description: Create bulkified triggers with handler patterns that prevent recursion. Create bulkified triggers with handler patterns that prevent recursion. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### SalesQL Enrichment Agent - Route: https://agentshelf.ai/discover/salesql-enrichment-agent - Category: data_analysis - Featured: No - Pricing: Freemium - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.8 - Rating Count: 67 - Installs: 0 - Created At: 2025-12-08T19:08:39.971Z Tagline: Enrich person and company data using SalesQL API with email and LinkedIn-based lookups. Short Description: Enrich person and company data using SalesQL API with email and LinkedIn-based lookups. Enrich person and company data using SalesQL API with email and LinkedIn-based lookups. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Search Result Parser Agent - Route: https://agentshelf.ai/discover/search-result-parser-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.6 - Rating Count: 34 - Installs: 0 - Created At: 2025-12-08T19:08:41.128Z Tagline: Execute web searches and parse results from Google, Bing, and DuckDuckGo. Short Description: Execute web searches and parse results from Google, Bing, and DuckDuckGo. Execute web searches and parse results from Google, Bing, and DuckDuckGo. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Skill Creator - Route: https://agentshelf.ai/discover/skill-creator - Category: development - Featured: No - Pricing: Free - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 34 - Installs: 0 - Created At: 2025-12-06T01:03:44.792Z Tagline: Create new Claude skills with proper structure, documentation, and validation. Short Description: Create new Claude skills with proper structure, documentation, and validation. Create new Claude skills with proper structure, documentation, and validation. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Spreadsheet Analyst - Route: https://agentshelf.ai/discover/spreadsheet-analyst - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: Yes - Rating: 4.5 - Rating Count: 95 - Installs: 0 - Created At: 2025-12-06T01:03:42.388Z - Tags: Spreadsheets, Excel, Google Sheets, Reporting, Analytics, Data Tagline: Turn spreadsheets into insights Short Description: Analyze Excel data with formulas, pivot tables, charts, and automated insights. Transform raw spreadsheet data into actionable insights. Create pivot tables, generate charts, write complex formulas, and automate repetitive analysis tasks. Perfect For: Analysts Time Savings: Hours of manual work → Minutes Result: Automated reports, instant insights Traditional: 2-4 hours AgentShelf: 10 minutes Improvement: 90% #### Key Features - Formula Writing: Create complex Excel/Sheets formulas automatically - Pivot Tables: Generate and customize pivot tables for analysis - Chart Generation: Create visualizations from your data - Data Cleaning: Automatically clean and format messy data ### Summarization Agent - Route: https://agentshelf.ai/discover/summarization-agent - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.8 - Rating Count: 39 - Installs: 0 - Created At: 2025-12-08T19:08:41.603Z Tagline: Generate concise summaries with multiple modes including executive and bullet formats. Short Description: Generate concise summaries with multiple modes including executive and bullet formats. Generate concise summaries with multiple modes including executive and bullet formats. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Token Optimizer Agent - Route: https://agentshelf.ai/discover/token-optimizer-agent - Category: development - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.8 - Rating Count: 22 - Installs: 0 - Created At: 2025-12-08T19:08:41.932Z Tagline: Optimize token usage across LLM operations with budget management and cost estimation. Short Description: Optimize token usage across LLM operations with budget management and cost estimation. Optimize token usage across LLM operations with budget management and cost estimation. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Web App Tester - Route: https://agentshelf.ai/discover/web-app-tester - Category: development - Featured: No - Pricing: Free - Publisher: Sarah Chen - Publisher Verified: No - Rating: 4.6 - Rating Count: 98 - Installs: 0 - Created At: 2025-12-06T01:03:43.937Z Tagline: Test web applications for accessibility, responsive design, and link integrity. Short Description: Test web applications for accessibility, responsive design, and link integrity. Test web applications for accessibility, responsive design, and link integrity. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Web Asset Generator - Route: https://agentshelf.ai/discover/web-asset-generator - Category: design - Featured: No - Pricing: Free - Publisher: Emma Thompson - Publisher Verified: No - Rating: 4.7 - Rating Count: 103 - Installs: 0 - Created At: 2025-12-06T01:03:43.512Z Tagline: Generate favicons, app icons, and social media images in all required formats. Short Description: Generate favicons, app icons, and social media images in all required formats. Generate favicons, app icons, and social media images in all required formats. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Web Security Analyst - Route: https://agentshelf.ai/discover/web-security-analyst - Category: development - Featured: No - Pricing: Paid - Publisher: John Smith - Publisher Verified: No - Rating: 4.8 - Rating Count: 54 - Installs: 0 - Created At: 2025-12-06T01:03:44.233Z Tagline: Security testing with FFUF web fuzzing for endpoint discovery and vulnerability analysis. Short Description: Security testing with FFUF web fuzzing for endpoint discovery and vulnerability analysis. Security testing with FFUF web fuzzing for endpoint discovery and vulnerability analysis. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% ### Website Content Scraper - Route: https://agentshelf.ai/discover/website-content-scraper - Category: data_analysis - Featured: No - Pricing: Free - Publisher: Michael Brown - Publisher Verified: No - Rating: 4.7 - Rating Count: 43 - Installs: 0 - Created At: 2025-12-08T19:08:40.893Z Tagline: General-purpose website scraper handling JavaScript rendering and various page structures. Short Description: General-purpose website scraper handling JavaScript rendering and various page structures. General-purpose website scraper handling JavaScript rendering and various page structures. Perfect For: Your Team Time Savings: Save time, boost productivity Result: Get more done in less time Traditional: Hours AgentShelf: Minutes Improvement: 80% --- ## Dynamic Marketplace Content - Route Pattern: https://agentshelf.ai/discover/:slug - Current public marketplace exports in this file are sourced from the live marketplace API. - Agent detail routes are prerendered at build time and exported here as static text for LLM consumption. --- ## Published Blog Posts - Route Prefix: https://agentshelf.ai/blog ### Best Practices for Product Discovery with LLM Agents - Route: https://agentshelf.ai/blog/best-practices-for-product-discovery-with-llm-agents - Category: Insights - Published At: 2026-01-16T10:00:00Z - Read Time: 10 min - Author: Gabe Arce - Featured: Yes - Tags: product-discovery, llm, workflows, ai-tools - Excerpt: How to take a product concept from idea to development-ready backlog using AI-assisted workflows Most AI-assisted product work fails. Not because the models are bad, but because the process is. The capability is real. PMs can now document complex systems, synthesize scattered requirements, and generate development-ready specs in hours instead of weeks. But most teams aren't capturing that value. They're stuck in single-shot prompting: ask the model, take the output, ship it. This guide covers techniques for LLM-assisted product discovery. Whether you're new to AI-assisted workflows or looking to refine your approach, we'll cover patterns that actually work. A quick note on tooling: LLMs don't work in isolation. The patterns in this guide assume you're using AI tools that can access your files—whether that's an AI-IDE like Cursor or Windsurf, Claude with file uploads, or ChatGPT with document attachments. The LLM provides the reasoning; the tooling provides access to your codebase, documents, and context. Without that scaffolding, most of what follows isn't possible. ## Core Principles Before diving into the workflow, three principles govern everything that follows. ### The Verification Problem LLMs are remarkably good at this work. Point a frontier model at a codebase, a set of requirements, or a collection of mockups, and it will produce spec documents that are largely accurate. The core architecture, the main user flows, the primary data models—these get captured well. With the right prompting, you can get 80-90% of the way there in a single pass. But that remaining percentage matters. The blind spots are subtle: a file path that doesn't quite exist, an edge case the model glossed over, an assumption that seemed reasonable but doesn't match reality. These aren't failures of intelligence—they're the inevitable result of synthesizing complex systems under uncertainty. Every spec has them. The question is whether you find them before development starts or after. :::info **Here's the core insight: an LLM can't objectively review its own work.** It's like asking someone to proofread their own essay immediately after writing it. They see what they meant to write, not what's actually on the page. An LLM that just wrote a spec has already weighted its context toward that output—mathematically, it's biased toward consistency rather than fresh verification. ::: The fix: start a fresh conversation for verification. In a new chat, the model approaches your document cold, spinning up subagents to verify claims against actual source material rather than defending what it previously generated. ### Cross-LLM Validation Fresh conversations catch blind spots within a single model. Cross-LLM validation catches blind spots across models. :::tip When you have a draft spec, run it through multiple AI models and collect independent feedback. Claude might catch an architectural inconsistency. Gemini flags missing error handling. GPT identifies an unrealistic timeline. The union of their feedback is more comprehensive than any single review. ::: Don't merge feedback blindly. Return to your original conversation and present the feedback as "colleague input." The original LLM, with full context of how the document was built, can evaluate what's valid and what isn't. Two to three rounds typically produces stable output. You're done when feedback becomes stylistic rather than substantive. ### The Human's Job LLMs handle generation. You handle judgment. Review, don't rubber-stamp. AI-generated specs can look polished while being subtly wrong. Read carefully. Trace the logic. Inject domain knowledge. You know things about the business, the users, the constraints that aren't in any document. The LLM can't know the VP of Sales promised a customer this feature would work a specific way. Make decisions. The LLM surfaces options. You choose direction. Quick solution now or robust approach upfront? That's a product decision, not a technical one. Challenge assumptions. When the approach doesn't feel right, push back. Your intuition is pattern-matching on experience. It's often detecting something real. These principles—fresh-conversation verification, cross-LLM validation, and human judgment—apply at every phase of the workflow. ## The Workflow With principles established, here's the workflow itself. Each phase builds on the previous, producing artifacts that feed the next. ### Phase 1: Document Current State :::warning Most product work fails because people skip understanding what exists. You can't plan where you're going without knowing where you are. ::: Everyone wants to jump to the new feature, the redesign, the migration. But you can't plan where you're going without knowing where you are. And "where you are" in a mature codebase is usually messier than anyone remembers. With the appropriate agent scaffolding, LLMs excel at codebase archaeology. They can read documentation, trace component hierarchies, map data flows, and surface technical debt nobody's discussed in years. Let them do this work. Generate the document: Point your AI tool at the area you're changing. Be specific: architecture, file paths, data models, API endpoints, integration points, known limitations. Then verify. Open a fresh conversation, provide access to the same files, and have it validate every claim in your freshly created spec doc. File paths should exist. Component descriptions should match implementations. Then review yourself. This is your chance to learn the system you're about to change. Domain knowledge catches errors LLMs miss. Output: A current-state document that accurately describes what exists today. ### Phase 2: Document Proposed State Product inputs come in many forms. Figma exports. PRDs written by committee. Technical RFCs. Slack threads where decisions were supposedly made. LLMs can synthesize all of it—but you need to provide the inputs and match the analytical lens to the input type. For mockups, prompt from a UI/UX perspective: component hierarchy, interactions, empty states, error states. For requirements docs, think like a product analyst: user flows, business rules, success criteria. For RFCs, adopt the architect lens: system boundaries, data flows, API contracts. Don't just summarize. Extract structure. What components exist? What data do they need? What can go wrong? Challenge and augment before finalizing. Push on vague areas. Then verify in a fresh conversation against the original materials. Output: A proposed-state document that captures design intent and requirements. ### Phase 3: Create Technical Specification Now bridge the gap. Feed the LLM both documents—current state and proposed state—and have it synthesize a technical specification. This is where the LLM earns its keep. It can identify what needs to change, what can stay, what new components are required, and how they integrate with existing systems. Architecture changes, data model updates, API modifications, migration strategies—all derived from the delta between where you are and where you're going. This document needs the most scrutiny. Apply cross-LLM validation here. Run the spec through multiple models. Collect feedback separately. Integrate what's valid. Repeat until the feedback stabilizes. Output: A technical specification describing how to get from current to proposed state. ### Phase 4: Decompose into Work Items Once you have a validated spec, have the LLM decompose the work into backlog items. The structure that works: Epic → Features → PBIs (or in Jira: Initiative → Epic → Stories). One Epic for the initiative. Features for capability groupings. PBIs for individual units a developer can complete. :::info **What makes a good PBI:** - **Single responsibility:** One clear deliverable - **Clear acceptance criteria:** Given/When/Then scenarios remove ambiguity - **Explicit dependencies:** "Blocked by" and "Blocks" relationships prevent false starts - **Sufficient detail:** Enough for a developer to begin without a lengthy briefing ::: Keep effort sizing simple. S/M/L based on complexity. Let the LLM propose; adjust based on your team's velocity. Validate the breakdown. Cross-LLM review catches circular dependencies, missing tasks, and unrealistic estimates. The work breakdown drives sprint planning—errors here create blocked sprints. Output: A structured backlog ready for development. ## Developing Your Workflow Start simple. Don't build an elaborate process before you've validated any of it works. Add verification steps when you notice recurring mistakes. Document what works. Standardize naming and folder structures—consistency enables automation. The meta-pattern: use the same iterative, validation-heavy approach to improve your process that you use to improve your specs. ## What's Next LLM-assisted product work is still early. The patterns will evolve as models improve. But the core principles will remain: verification through fresh conversations, cross-model validation, human judgment where business context matters. The productivity gains are real. Specs that took weeks now take days. Specs that would typically be shallow are now comprehensive. Edge cases caught in planning instead of QA. Start experimenting. The cost of trying is low. The cost of waiting is higher. Coming soon: The Artifacts That Power AI Agents—a deep dive into the documents this workflow produces and how they enable AI-assisted development. We'll cover how structured specs like current-state analyses, technical specifications, and detailed PBIs become the foundation for AI tools that can implement features with minimal hand-holding. *First Published on [LinkedIn](https://www.linkedin.com/pulse/best-practices-product-discovery-llm-agents-gabe-arce-qqnxc/)* ### The Rise of Digital Workers: Understanding AI Agents Beyond the LLM - Route: https://agentshelf.ai/blog/understanding-ai-agents-beyond-the-llm - Category: Insights - Published At: 2026-01-09T10:00:00Z - Read Time: 12 min - Author: Gabe Arce - Tags: ai-agents, llm, enterprise, multi-agent - Excerpt: LLMs are minds. Agents are workers. Understanding this distinction is the key to deploying AI that actually delivers value. Over the last six months, as I built and iterated on AI agents, I found myself reaching for the same playbook I'd used for years onboarding team members. It wasn't intentional at first, more instinct than strategy, but it worked. I've spent my career scaling technical teams. I know the grind of getting someone from "just joined" to "delivering value" in 30 days or less. The things that make that possible—clear protocols, documented standards, well-defined guardrails—turn out to be the same things that make agents effective. Turns out, an agent without clear context is lost, just like a new hire thrown into the deep end. An agent with too broad a scope thrashes, just like an employee who doesn't know what's expected. Agents aren't magic. They're new workers, and they need to be onboarded the same way. ## The Confusion: LLMs vs. Agents Everyone's talking about AI. Few are precise about what they mean. :::info **LLMs are minds. Agents are workers.** This distinction is the key to understanding how to deploy AI that actually delivers value. ::: An LLM, a large language model, is raw intelligence. It can reason, synthesize, and generate with remarkable capability. But it's stateless. Every conversation starts from zero, with no memory of your last interaction. It can't open a file, run a command, or check your calendar. It can't do anything; it can only say things. Think of an LLM as a brilliant consultant who forgets you the moment you leave the room. An agent is what happens when you give that consultant context, a set of tools, and permission to act. Context gives it continuity, so it actually knows your business. Tools give it hands, so it doesn't just suggest but executes. Autonomy lets it break goals into steps, try things, observe results, and adjust. That loop is what turns intelligence into labor. ## The God-Agent Fallacy There's a persistent dream in the AI world: the god-agent. One monolithic system that does everything. Plug it in, ask, and it delivers. No configuration, no specialization, no thought required. :::warning This is the implicit promise behind most enterprise AI pitches, and it's why so many implementations disappoint. The gap isn't in the technology—it's in the approach. ::: There is simply too much information in the world for an LLM to navigate without guidance. Too many possible paths, too much ambiguity. Look at the major players: Microsoft's Copilot, Salesforce's Agentforce. They're hitting massive hurdles, not because the models aren't capable, but because they're chasing the god-agent dream while burying users in complexity and abstraction. The better path is to let domain experts build domain agents. The people who know "good" are the specialists who live it daily. A senior engineer knows clean code in their codebase. A financial analyst knows a sound model in their industry. These are the people who should be building agents, and when they do, the result is more reliable, higher-quality outcomes. ## The Better Path: Focused Agents An LLM knows, in some sense, everything. It's been trained on enormous amounts of text, images, audio, and video—essentially, the sum of published human knowledge. That breadth is a feature when you're having a conversation, but it's a liability when you're trying to get work done. Effective agents are focused. Like a good employee, they know their role, understand their boundaries, and have what they need to perform. You don't hire a generalist and hope for the best. You hire a specialist and set them up for success. This requires a three-layer architecture. The first layer is the system prompt, the agent's identity document. It defines the domain, the role, and the boundaries. Think of it as the job description and mission statement combined: strategic, not exhaustive. The second layer is context. This includes documentation, standards, reference material, and memory of past interactions. The agent doesn't carry all of it at once. It knows where to look and pulls what it needs, keeping active context lean while making depth available. The third layer is the execution environment, a space where the agent can actually run the tools available to it. Without this, an agent can only talk. With it, an agent can work. :::tip **Constraint enables performance.** Broad agents are bad agents. When scope is too wide, they wander, hallucinate relevance, and produce mediocre work. Tight grounding plus accessible depth equals focused execution. ::: How narrow should you go? It depends on the magnitude of the work. Building a simple application with 20 files? A frontend agent and a backend agent might be enough. Building an enterprise platform with thousands of files? You need an organization of agents, with teams mapped to modules and further specialization within each team. Agent architecture should mirror work architecture. ## Teams Beat Solo Performers The best individual contributor will always lose to a well-coordinated team on complex work. The same applies to agents. A single agent has limits. It can hold only so much context, specialize in only so many domains. When work gets complex, a solo agent breaks down. But a team of specialized agents working together is a different story. Real work gets completed through handoffs. Someone researches, someone drafts, someone reviews, someone executes. Agent teams work the same way: one gathers requirements, another generates a first draft, a third validates against standards, a fourth handles delivery. Each stays focused on its specialty, and together they deliver what none could alone. The key is orchestration. You need a way to coordinate specialized agents toward a shared outcome, and that orchestration doesn't require code. You describe what you need in plain language, and the orchestrator breaks the task into steps, identifies which agents are needed, and mobilizes them. This is how enterprises will scale AI: not with one do-everything agent, but with teams of focused agents working in concert. ## The Shift: From Assistant to Colleague Stop thinking of agents as just smart assistants. Start thinking of them as digital workers. The difference is subtle, but profound. You don't ask an assistant to own a project, but a worker gets assigned outcomes. A worker operates asynchronously, in the background, while you do other things. A worker can be held accountable. When you adopt this frame, your relationship changes. You're not prompting anymore; you're delegating. That means getting clear on what success looks like, providing the right context, and checking work until trust is built. It's the same way you'd manage any new hire. ## The Barriers, and What We're Building Everything I've described requires serious infrastructure. Context management, provider failover, cost tracking, security boundaries, audit trails. Building this from scratch can take 12–18 months and millions in engineering. Most organizations don't have that runway. Meanwhile, the AI landscape keeps shifting. The best model today won't be the best model next quarter. Locking into a single provider is a strategic risk. This is why we built AgentShelf.ai. AgentShelf is production-ready AI infrastructure for the enterprise. Seven providers behind one API, with automatic failover when something breaks. You're not locked in; you route to the right model for each task, and switch when better options emerge. For business teams, it means building agents without code. You describe what you need in plain language: the context, the tools, the standards. The platform handles the rest. Managers can build custom agents and distribute them to their teams, so everyone works from the same playbook. For leadership, it means visibility and control. The telemetry layer shows you what the LLM is actually doing on each request, and gives the organization a clear picture of where, when, and how agents are being used across teams. You see cost, performance, and adoption patterns in real time, with the audit trail compliance requires. Security is enterprise-grade: data encrypted at rest and in transit, SOC 2 readiness, and full tenant isolation. The choice isn't whether to adopt AI. It's how. You can spend 12 plus months building infrastructure from scratch, with no guarantee you're building the right thing. You can cobble together scattered AI services that each solve part of the problem but never integrate cleanly. Or you can go to production in weeks with infrastructure that's already figured out. ## What This Means for Organizations When agents handle execution, humans focus on judgment. Repetitive, well-defined tasks become agent work while creative and strategic tasks stay human. This isn't replacement; it's reallocation. Agents also scale differently than humans. They run in parallel and don't need sleep. The economics shift dramatically. But new risks emerge too. :::warning Agents move fast, which means they can break things fast. Guardrails, checkpoints, and human oversight aren't bureaucracy—they're essential infrastructure. ::: The ability to design, deploy, and orchestrate agents is becoming a core competency. The organizations that develop it first will have a serious advantage. ## Conclusion: From Intelligence to Labor LLMs gave us artificial intelligence: the ability to reason, synthesize, and generate at scale. But intelligence alone isn't labor. Agents gave us the next step. They're artificial workers: intelligence wrapped in context, tools, and the capacity to act. Not minds in isolation, but minds in harness. Build focused agents. Ground them in real expertise. Give them the tools they need and scope them to work they can actually do well. Orchestrate them into teams, and manage them like what they are: your newest team members. The digital worker has arrived. What matters now is how you put them to work. *First Published on [LinkedIn](https://www.linkedin.com/pulse/rise-digital-workers-understanding-ai-agents-beyond-llm-gabe-arce-hry1c/)* --- ## Privacy Policy - Route: https://agentshelf.ai/legal/privacy-policy - SEO Title: Privacy Policy | AgentShelf - SEO Description: Learn how AgentShelf collects, uses, and protects your personal information. # PRIVACY POLICY **Effective Date:** December 2, 2025 **Version:** 1.1.0 (Beta) **Last Updated:** December 2, 2025 --- ## Introduction This Privacy Policy describes how Talavera Solutions LLC, doing business as AgentShelf.ai ("AgentShelf," "we," "us," or "our"), collects, uses, stores, shares, and protects your information when you use our AI agent management platform (the "Service"). Your privacy is important to us. We are committed to protecting your personal data and handling it responsibly. This policy explains our data practices in a transparent manner so you can make informed decisions about using our Service. By accessing or using our Service, you agree to the terms of this Privacy Policy and our Terms of Service. If you do not agree with the practices described in this policy, please do not use our Service. **BETA NOTICE:** AgentShelf.ai is currently in beta. During this period, we may modify our data practices as we refine the Service. We will notify you of any material changes to this Privacy Policy. --- ## Table of Contents 1. [Information We Collect](#1-information-we-collect) 2. [How We Use Your Information](#2-how-we-use-your-information) 3. [Data Transmission to LLM Providers](#3-data-transmission-to-llm-providers) 4. [How We Share Your Information](#4-how-we-share-your-information) 5. [Data Security](#5-data-security) 6. [Data Retention](#6-data-retention) 7. [Your Rights and Choices](#7-your-rights-and-choices) 8. [International Data Transfers](#8-international-data-transfers) 9. [Children's Privacy](#9-childrens-privacy) 10. [Cookies and Tracking Technologies](#10-cookies-and-tracking-technologies) 11. [Third-Party Links and Services](#11-third-party-links-and-services) 12. [California Privacy Rights (CCPA)](#12-california-privacy-rights-ccpa) 13. [European Privacy Rights (GDPR)](#13-european-privacy-rights-gdpr) 14. [Changes to This Privacy Policy](#14-changes-to-this-privacy-policy) 15. [Contact Us](#15-contact-us) --- ## 1. Information We Collect We collect various types of information to provide and improve our Service. This data falls into the following categories: ### 1.1 Account Information When you register for an account, we collect personal information you provide directly to us: | Data Type | Examples | Purpose | |-----------|----------|---------| | **Identification Data** | Name, email address | Account creation, communication | | **Professional Data** | Company name, job title (optional) | Service personalization | | **Authentication Data** | Password (hashed), SSO credentials | Account security | | **Subscription Data** | Subscription tier, billing information | Service access, payment processing | | **Preferences** | UI settings, notification preferences, LLM access mode | Service customization | **Password Security:** We never store your password in plain text. Passwords are hashed using bcrypt with cryptographic salt before storage. ### 1.2 Agent and Workspace Data When you create and use Agents and Workspaces, we collect: **Agent Configurations:** - Agent name, description, and icon - System prompts and instructions - Tool configurations and quick actions - Tags and categorization - Visibility settings (private, team, public) - Marketplace submission data (if applicable) **Workspace Data:** - Chat messages (user inputs and AI responses) - Task data (descriptions, status, priorities, dependencies) - Knowledge graph relationships - Workspace settings and configurations **File Data:** - Uploaded files (documents, images, videos, audio) - File metadata (name, type, size, upload date) - SHA-256 hash (for deduplication) - Processing status and extracted content ### 1.3 Team and Collaboration Data When you participate in Teams, we collect: - Team membership and role assignments - Team invitations (email, invitation token, status) - Agent sharing permissions and history - Team workspace associations ### 1.4 Usage and Analytics Data We automatically collect information about how you interact with the Service: **LLM Usage Records:** | Data Point | Description | |------------|-------------| | Provider and model | Which LLM provider and model was used | | Token counts | Input, output, cache, and reasoning tokens | | Cost information | Provider cost, markup, billed amount | | Access mode | Managed or BYOK | | Latency metrics | Response time and processing duration | | Timestamps | When requests were made | **Platform Usage:** - Features accessed and frequency of use - Session duration and navigation patterns - Search queries within the Platform - Error logs and performance data ### 1.5 Technical Data We automatically collect technical information: - **Device Information:** IP address, browser type, operating system, device identifiers - **Connection Data:** Network information, referring URLs - **Log Data:** System logs, error reports, API access logs ### 1.6 API Keys (BYOK Mode) If you use BYOK (Bring Your Own Key) mode: - We collect and store your LLM provider API keys - API keys are encrypted using AES-256-GCM encryption - Keys are only decrypted at the moment of use - We never expose your full API keys in logs or responses --- ## 2. How We Use Your Information We use the information we collect for the following purposes: ### 2.1 Providing and Maintaining the Service - Creating and managing your account - Enabling Agent creation, configuration, and deployment - Facilitating Agent Workspace interactions and chat functionality - Processing file uploads and managing storage - Supporting Team collaboration and agent sharing - Operating the Marketplace for Agent discovery ### 2.2 Processing and Routing AI Requests - Transmitting your messages and files to LLM Providers to generate responses - Managing API key authentication (Managed or BYOK mode) - Handling streaming responses and real-time updates - Tracking token usage for cost calculation and billing ### 2.3 Cost Tracking and Billing - Calculating costs based on LLM token usage - Enforcing budget limits and sending alerts - Generating usage reports and analytics - Processing payments (when billing is implemented) ### 2.4 Service Improvement and Analytics To improve our services, we analyze aggregated and anonymized data: - Feature usage patterns and popularity - Performance metrics and optimization opportunities - Error patterns and reliability improvements - User experience research **Important:** We will **never** use your private chat messages, Agent configurations, or uploaded files to train machine learning models without your explicit, opt-in consent. ### 2.5 Communication - Sending service-related notifications (account alerts, security notices) - Providing customer support and responding to inquiries - Sending product updates and announcements (with opt-out available) - Notifying you of changes to our Terms or Privacy Policy ### 2.6 Security and Fraud Prevention - Protecting the integrity and security of our Service - Detecting, preventing, and responding to security threats - Enforcing our Terms of Service and Acceptable Use Policy - Investigating suspicious or unauthorized activity ### 2.7 Legal Compliance - Complying with applicable laws and regulations - Responding to lawful requests from authorities - Establishing, exercising, or defending legal claims --- ## 3. Data Transmission to LLM Providers ### 3.1 How Your Data Flows to LLM Providers When you interact with an Agent, your data is transmitted to third-party LLM Providers: ``` User → AgentShelf Platform → LLM Provider → AgentShelf Platform → User ``` **Data Transmitted:** - Chat messages (your inputs) - System prompts (Agent configuration) - Uploaded files or file content (when attached to conversations) - Context from previous messages in the conversation ### 3.2 Supported LLM Providers We currently integrate with the following LLM Providers: | Provider | Models | Headquarters | |----------|--------|--------------| | **OpenAI** | GPT-4o, GPT-4o-mini, o1, o3 | United States | | **Anthropic** | Claude 4.5 Sonnet, Claude 4.5 Haiku, Claude Opus | United States | | **Google** | Gemini 2.5 Pro, Gemini 2.5 Flash | United States | | **xAI** | Grok 4, Grok 3 | United States | | **Azure OpenAI** | GPT-4o, GPT-4-turbo | Various (Azure regions) | | **DeepSeek** | V3.2, R1 | China | | **AWS Bedrock** | Claude 3.5 Sonnet, Claude 3.5 Haiku | Various (AWS regions) | ### 3.3 LLM Provider Data Practices and Model Training **Critical Disclosure:** Each LLM Provider has its own privacy policy and data practices regarding model training. By using our Service, you acknowledge and understand the following: #### Data Training Practices by Provider | Provider | Data Used for Training? | Opt-Out Available? | Notes | |----------|------------------------|-------------------|-------| | **OpenAI** | API data: Generally No | Yes (via API settings) | Enterprise/API customers typically excluded from training | | **Anthropic** | API data: No | N/A | Claude API data not used for training | | **Google** | Varies by service | Yes (via settings) | Review Gemini API terms for specifics | | **xAI** | Review current policy | Review policy | Policies may change | | **Azure OpenAI** | No | N/A | Microsoft enterprise commitment | | **DeepSeek** | Review current policy | Review policy | Based in China; review data handling | | **AWS Bedrock** | Provider-dependent | Provider-dependent | Depends on underlying model provider | **Important Notes:** - The above information is provided for general guidance only and may change - **You are responsible for reviewing current provider policies** before transmitting sensitive data - Policies may differ between consumer products and API services - Enterprise agreements may provide additional protections #### Your Compliance Obligations (BYOK Mode) **If you use BYOK (Bring Your Own Key) mode, you are directly responsible for:** - Reviewing and understanding your LLM Provider's data practices - Configuring any available privacy settings or opt-outs with your provider - Ensuring your use complies with your provider's terms of service - Informing your end users about data transmission to LLM Providers - Compliance with all applicable data protection regulations (GDPR, CCPA, etc.) **AgentShelf cannot guarantee** that LLM Providers will not use your data for training purposes. If data training is a concern for your use case, you should: 1. Review current provider policies directly (links below) 2. Consider enterprise-tier provider agreements with explicit no-training commitments 3. Avoid transmitting sensitive personal data or confidential information 4. Contact providers directly for written confirmation of data practices #### Provider Privacy Policy Links We recommend reviewing the privacy policies of LLM Providers you use: - [OpenAI Privacy Policy](https://openai.com/policies/privacy-policy/) - [OpenAI API Data Usage Policy](https://openai.com/policies/api-data-usage-policies/) - [Anthropic Privacy Policy](https://www.anthropic.com/legal/privacy) - [Google Privacy Policy](https://policies.google.com/privacy) - [Google Cloud Data Processing Terms](https://cloud.google.com/terms/data-processing-addendum) - [xAI Privacy Policy](https://x.ai/legal/privacy-policy) - [Microsoft Azure Data Protection](https://www.microsoft.com/licensing/docs/view/Microsoft-Products-and-Services-Data-Protection-Addendum-DPA) - [AWS Data Privacy](https://aws.amazon.com/compliance/data-privacy/) **Disclaimer:** AgentShelf is not responsible for LLM Provider data practices and makes no warranties regarding their compliance with any data protection regulations. ### 3.4 Managed Mode vs. BYOK Mode **Managed Mode:** - AgentShelf uses platform-managed API keys - We act as the customer of record with LLM Providers - Provider data practices apply to AgentShelf as the customer **BYOK Mode:** - You use your own API keys - You establish a direct relationship with the LLM Provider - Provider data practices apply to you as their direct customer - You may have more control over data handling through your provider account settings ### 3.5 Enterprise Data Protection For Enterprise customers, we offer enhanced data protections: - Your Content is treated as Confidential Information - Chat data is not used for any purpose beyond providing the Service - No anonymized data extraction or ML training use - Additional contractual protections available (DPA, BAA) Contact support@agentshelf.ai for Enterprise privacy options. --- ## 4. How We Share Your Information We do not sell your personal data to third parties. We may share your information only in the following circumstances: ### 4.1 With Your Consent We will share your information when you explicitly authorize us to do so. ### 4.2 Service Providers We may share data with third-party vendors who perform services on our behalf: | Service Type | Purpose | Data Shared | |--------------|---------|-------------| | **Cloud Infrastructure** | Data storage and processing | All platform data (encrypted) | | **LLM Providers** | AI response generation | Chat messages, files, prompts | | **Analytics** | Usage analysis and improvement | Anonymized usage data | | **Payment Processing** | Billing and payments (future) | Payment information | | **Email Services** | Transactional emails (future) | Email addresses, notification content | All service providers are contractually obligated to protect your data and use it only for the services they provide to us. ### 4.3 Team Collaboration When you participate in Teams: - Team administrators can see Team membership and roles - Shared Agent configurations are visible to Team members with appropriate permissions - Individual Workspace contents (chat history, files) remain private to each user ### 4.4 Marketplace If you publish an Agent to the Marketplace: - Your Agent's public configuration (name, description, category) is visible to all users - Your username or display name may be shown as the Agent creator - Usage statistics (downloads, ratings) are publicly visible ### 4.5 Legal Requirements We may disclose your information if required by law or if we believe in good faith that such disclosure is necessary to: - Comply with legal obligations, court orders, or government requests - Protect and defend our rights or property - Prevent or investigate possible wrongdoing - Protect the personal safety of users or the public - Protect against legal liability ### 4.6 Business Transfers In the event of a merger, acquisition, bankruptcy, or sale of all or a portion of our assets: - Your information may be transferred to the acquiring entity - We will provide notice before your information becomes subject to a different privacy policy - You will have the opportunity to delete your account before such transfer --- ## 5. Data Security We implement industry-standard security measures to protect your data from unauthorized access, use, or disclosure. ### 5.1 Encryption | Data State | Encryption Method | |------------|-------------------| | **API Keys (BYOK)** | AES-256-GCM with PBKDF2 key derivation | | **Passwords** | bcrypt with cryptographic salt | | **Data in Transit** | TLS/SSL encryption | | **Data at Rest** | Database encryption (planned enhancement) | ### 5.2 Access Controls - Role-based access control (RBAC) for platform resources - JWT-based authentication with token expiration - Account lockout after failed login attempts - Session management and token blacklisting ### 5.3 Infrastructure Security - Cloud infrastructure with security certifications - Network isolation and firewall protection - Regular security assessments and monitoring - Incident response procedures ### 5.4 Security Limitations While we implement reasonable security measures, no method of transmission or storage is 100% secure. We cannot guarantee absolute security of your data. You are responsible for: - Maintaining the confidentiality of your account credentials - Using strong, unique passwords - Securing your own API keys (BYOK mode) - Reporting security vulnerabilities to support@agentshelf.ai ### 5.5 Security Roadmap (Beta) The following security enhancements are planned: - Multi-factor authentication (MFA) - Enhanced encryption at rest for all user data - Advanced audit logging - SOC 2 Type II certification (in progress) - Additional compliance certifications based on customer needs --- ## 6. Data Retention ### 6.1 Active Account Data We retain your data for as long as your account is active and as needed to provide the Service: | Data Type | Retention Period | |-----------|------------------| | Account Information | Duration of account + 30 days after deletion | | Agent Configurations | Duration of account or until deleted | | Chat Messages | Duration of account or until Workspace deleted | | Uploaded Files | Duration of account or until deleted | | Usage Records | 24 months for billing and analytics | | Audit Logs | 12 months | ### 6.2 Account Deletion Upon receiving a deletion request: 1. Your account will be deactivated immediately 2. Personal data will be permanently deleted within **30 days** 3. Backups containing your data will be purged within **90 days** 4. Anonymized, aggregated data may be retained indefinitely **Note:** We may retain certain data as required by law (e.g., billing records for tax purposes). ### 6.3 Data Deletion Requests To request deletion of your data: 1. Email support@agentshelf.ai with subject "Data Deletion Request" 2. Include your registered email address for verification 3. Specify if you want complete account deletion or specific data removal 4. We will process your request within 30 days ### 6.4 Team Data - When a Team Owner deletes a Team, associated Team data is deleted - Individual user data within Team Workspaces is retained until the user deletes it - Departed Team members retain their individual Workspace data --- ## 7. Your Rights and Choices You have several rights regarding your personal data: ### 7.1 Access and Portability - **Access:** You can access your account information through your account settings - **Download:** You can export your data (feature planned for future release) - **Usage Reports:** You can view your LLM usage and cost history in the Platform ### 7.2 Correction You can update your account information at any time through: - Account settings in the Platform ### 7.3 Deletion You have the right to request deletion of your personal data: - Delete individual Agents, Workspaces, or files through the Platform - Request complete account deletion via support@agentshelf.ai - Deletion requests are processed within 30 days ### 7.4 Restriction and Objection You may request that we: - Restrict processing of your data in certain circumstances - Stop using your data for specific purposes - Object to automated decision-making (if applicable) ### 7.5 Communication Preferences You can manage your communication preferences: - **Marketing Emails:** Unsubscribe via link in emails or account settings - **Service Notifications:** Essential notifications cannot be disabled while account is active - **Team Notifications:** Configure in Team settings ### 7.6 Data Processing Opt-Out You may opt out of having your data used for service improvement: - Contact support@agentshelf.ai to opt out - Note: This does not affect data processing necessary to provide the Service --- ## 8. International Data Transfers ### 8.1 Data Location Our primary data processing and storage facilities are located in the **United States**. Your information may be transferred to, and processed in, the United States and other countries where our service providers operate. ### 8.2 Transfer Mechanisms and Safeguards For international data transfers, we employ appropriate safeguards as required by applicable law: **For transfers from the European Economic Area (EEA), United Kingdom, and Switzerland:** | Mechanism | Description | When Used | |-----------|-------------|-----------| | **EU-US Data Privacy Framework** | Certification under the EU-US Data Privacy Framework (where applicable) | US service providers certified under DPF | | **Standard Contractual Clauses (SCCs)** | EU Commission-approved contractual terms for data transfers | Transfers to countries without adequacy decisions | | **UK International Data Transfer Agreement** | UK-specific addendum to SCCs | Transfers from UK | | **Swiss-US Data Privacy Framework** | Framework for Swiss data transfers | Transfers from Switzerland | **Additional Safeguards:** - Data Processing Agreements (DPAs) with all sub-processors - Technical and organizational security measures (see Section 5) - Regular review of transfer mechanisms for legal compliance - Supplementary measures where required by law ### 8.3 Sub-Processor Locations Our primary service providers and their locations: | Service Provider | Purpose | Primary Location | |-----------------|---------|------------------| | Cloud Infrastructure | Data storage and processing | United States | | LLM Providers | AI response generation | See Section 3.2 | | Analytics Services | Usage analytics | United States | ### 8.4 LLM Provider Data Transfers Data transmitted to LLM Providers may be processed in various locations depending on the provider's infrastructure: | Provider | Primary Processing Locations | |----------|------------------------------| | OpenAI | United States | | Anthropic | United States | | Google | United States, Global | | xAI | United States | | Azure OpenAI | Configurable (Azure regions) | | DeepSeek | China | | AWS Bedrock | Configurable (AWS regions) | **Important:** When using DeepSeek or other providers based outside your jurisdiction, your data may be subject to different legal frameworks. **You are responsible for ensuring compliance** with your organization's data residency requirements. ### 8.5 Your Rights Regarding Transfers If you are located in the EEA, UK, or Switzerland, you have the right to: - Request information about the safeguards in place for international transfers - Obtain a copy of the Standard Contractual Clauses we use - Lodge a complaint with your local supervisory authority ### 8.6 Consent to Transfer By using the Service, you consent to the transfer of your data to the United States and other jurisdictions that may have different data protection laws than your country of residence. **For EU/EEA Users:** Where we rely on consent as a legal basis for transfer, you may withdraw your consent at any time by discontinuing use of the Service. However, withdrawal of consent does not affect the lawfulness of processing based on consent before its withdrawal. --- ## 9. Children's Privacy Our Service is not intended for use by individuals under the age of **18**. - We do not knowingly collect personal information from children under 18 - If we become aware that we have collected data from a child under 18, we will take steps to delete that information promptly - If you are a parent or guardian and believe your child has provided us with personal information, please contact us at support@agentshelf.ai --- ## 10. Cookies and Tracking Technologies ### 10.1 What We Use We use cookies and similar technologies to enhance your experience: | Technology | Purpose | Duration | |------------|---------|----------| | **Session Cookies** | Authentication, maintaining login state | Session | | **Preference Cookies** | Remembering your settings | Persistent | | **Analytics Cookies** | Understanding usage patterns | Persistent | | **Security Cookies** | Fraud prevention, security | Session | ### 10.2 Cookie Management You can control cookies through your browser settings: - Most browsers allow you to refuse cookies or delete existing cookies - Blocking cookies may limit your ability to use certain features of the Service - Essential cookies required for authentication cannot be disabled ### 10.3 Do Not Track We currently do not respond to "Do Not Track" browser signals as there is no industry standard for compliance. --- ## 11. Third-Party Links and Services ### 11.1 External Links The Service may contain links to third-party websites or services that are not owned or controlled by AgentShelf. We are not responsible for: - The privacy practices of third-party sites - Content on third-party sites - Any damages arising from your use of third-party services ### 11.2 LLM Provider Services Your use of LLM Provider services through our Platform is subject to their respective terms and privacy policies. We encourage you to review these policies before using specific providers. --- ## 12. California Privacy Rights (CCPA) If you are a California resident, you have additional rights under the California Consumer Privacy Act (CCPA): ### 12.1 Right to Know You have the right to request information about: - Categories of personal information we collect - Sources of personal information - Business purposes for collecting personal information - Categories of third parties with whom we share personal information - Specific pieces of personal information we have collected about you ### 12.2 Right to Delete You have the right to request deletion of your personal information, subject to certain exceptions. ### 12.3 Right to Non-Discrimination We will not discriminate against you for exercising your CCPA rights. ### 12.4 Categories of Information Collected In the past 12 months, we have collected the following categories of personal information: - Identifiers (name, email, IP address) - Commercial information (subscription data, usage records) - Internet activity (browsing history within the Platform, search queries) - Professional information (job title, company name) - Inferences (preferences based on usage patterns) ### 12.5 Sale of Personal Information We do not sell personal information as defined by the CCPA. ### 12.6 Exercising Your Rights To exercise your CCPA rights, contact us at: - Email: support@agentshelf.ai - Include "CCPA Request" in the subject line We will verify your identity before processing your request. --- ## 13. European Privacy Rights (GDPR) If you are located in the European Economic Area (EEA), United Kingdom, or Switzerland, you have additional rights under the General Data Protection Regulation (GDPR): ### 13.1 Legal Bases for Processing We process your data based on the following legal bases: | Purpose | Legal Basis | |---------|-------------| | Providing the Service | Contract performance | | Account management | Contract performance | | Security and fraud prevention | Legitimate interests | | Service improvement | Legitimate interests | | Marketing communications | Consent | | Legal compliance | Legal obligation | ### 13.2 Your GDPR Rights - **Right of Access:** Obtain confirmation of processing and access to your data - **Right to Rectification:** Correct inaccurate or incomplete data - **Right to Erasure:** Request deletion of your data ("right to be forgotten") - **Right to Restriction:** Restrict processing in certain circumstances - **Right to Data Portability:** Receive your data in a structured, machine-readable format - **Right to Object:** Object to processing based on legitimate interests - **Right to Withdraw Consent:** Withdraw consent at any time (where processing is based on consent) ### 13.3 Data Protection Officer For GDPR-related inquiries, contact: - Email: support@agentshelf.ai ### 13.4 Supervisory Authority You have the right to lodge a complaint with a supervisory authority in your country of residence if you believe our processing of your data violates applicable law. ### 13.5 Data Processing Agreements Enterprise customers may request a Data Processing Agreement (DPA) that complies with GDPR requirements. Contact support@agentshelf.ai. --- ## 14. Changes to This Privacy Policy We may update this Privacy Policy from time to time to reflect changes in our practices or applicable laws. ### 14.1 Definition of Material Changes A change is considered **"material"** if it: - **Expands data collection:** Introduces new categories of personal data we collect - **Changes data use:** Uses your data for new purposes not previously disclosed - **Adds third-party sharing:** Shares your data with new categories of third parties - **Modifies retention periods:** Significantly extends how long we retain your data - **Reduces your rights:** Limits your rights or choices regarding your data - **Changes security practices:** Materially reduces the security measures protecting your data - **Adds LLM providers:** Integrates new LLM providers that process your data - **Modifies data training practices:** Changes whether or how your data may be used for AI training - **Affects international transfers:** Changes the countries or mechanisms for international data transfers ### 14.2 Notification of Changes **For Material Changes:** - We will provide at least **30 days' advance notice** before material changes take effect - Notice will be sent via email to your registered email address - A prominent banner will be displayed within the Platform - For significant changes affecting data rights, we may require re-acceptance **For Non-Material Changes:** - We will update the "Last Updated" date at the top of this document - Changes will be posted on our website - We encourage you to review periodically ### 14.3 Your Continued Use Your continued use of the Service after the effective date of any changes constitutes your acceptance of the revised Privacy Policy. If you do not agree with the revised policy, you must discontinue use of the Service. ### 14.4 Access to Previous Versions Upon request, we will provide you with previous versions of this Privacy Policy. Contact support@agentshelf.ai. ### 14.5 Review Recommendation We encourage you to review this Privacy Policy periodically to stay informed about our data practices. We will maintain a version history of significant changes. --- ## 15. Contact Us If you have any questions, concerns, or requests regarding this Privacy Policy or our data practices, please contact us: **Talavera Solutions LLC** d/b/a AgentShelf.ai | Purpose | Contact | |---------|---------| | **General Privacy Questions** | support@agentshelf.ai | | **Data Subject Requests** | support@agentshelf.ai | | **Security Concerns** | support@agentshelf.ai | | **GDPR/DPO Inquiries** | support@agentshelf.ai | | **Enterprise Privacy** | support@agentshelf.ai | | **General Support** | support@agentshelf.ai | **Response Time:** We aim to respond to all privacy-related inquiries within 30 days. --- ## Summary of Key Points | Topic | Summary | |-------|---------| | **What we collect** | Account info, Agent/Workspace data, usage analytics, files | | **How we use it** | Providing Service, AI processing, cost tracking, improvement | | **LLM Providers** | Data transmitted to generate AI responses; subject to their policies | | **Sharing** | Service providers, legal requirements; we do not sell data | | **Security** | Encryption, access controls, security monitoring | | **Your rights** | Access, correction, deletion, data portability | | **Retention** | Active account duration + 30 days after deletion | | **International** | Data processed in US; safeguards for international transfers | --- **Version:** 1.1.0 (Beta) **Effective Date:** December 2, 2025 **Document Owner:** Talavera Solutions LLC --- ## Terms of Service - Route: https://agentshelf.ai/legal/terms-and-conditions - SEO Title: Terms of Service | AgentShelf - SEO Description: Understand your rights and responsibilities when using AgentShelf. # TERMS OF SERVICE **Effective Date:** December 2, 2025 **Version:** 1.1.0 (Beta) **Last Updated:** December 2, 2025 --- The Terms of Service ("ToS" or "Agreement") for AgentShelf.ai is a legally binding agreement between you (the "User") and Talavera Solutions LLC ("AgentShelf," "we," "us," or "our"). This document outlines your rights and responsibilities when using our AI agent management platform and services. Please read this agreement carefully before accessing or using AgentShelf.ai. **BETA NOTICE:** AgentShelf.ai is currently in beta. During this period, certain features may be limited, modified, or discontinued. By participating in our beta program, you acknowledge and accept that the Service is provided on an "as-is" basis with no guarantees of availability, completeness, or final feature sets. --- ## 1. Introduction This Agreement, along with our Privacy Policy, governs your access to and use of the AgentShelf.ai platform, including all associated websites, services, APIs, and applications (collectively, the "Service"). By creating an account or using the Service, you agree to be bound by these Terms of Service. If you do not agree to these terms, you may not use the Service. AgentShelf.ai is an AI agent management platform that enables users to create, configure, deploy, and manage AI-powered assistants ("Agents") across multiple large language model (LLM) providers. The platform facilitates team collaboration, workspace management, and cost tracking for AI interactions. --- ## 2. Definitions To ensure clarity, the following key terms are used throughout this document: - **"Platform"** refers to the AgentShelf.ai website, application, APIs, and all related services, features, and functionality. - **"User"** or **"You"** means any individual, team, or entity accessing or using the Service. - **"Agent"** means an AI assistant configured within the Platform, including its system prompts, tool configurations, quick actions, and associated settings. - **"Agent Workspace"** means the isolated environment where a User interacts with a specific Agent, including chat history, tasks, files, and knowledge graphs. - **"Content"** means any data, text, prompts, configurations, files, and other materials that you create, upload, post, or otherwise provide to the Platform. This includes Agent configurations, chat messages, uploaded files, and task data. - **"User Content"** means Content specifically created or uploaded by you, including but not limited to Agent configurations, system prompts, workspace files, and chat interactions (inputs to the Service). - **"Output"** or **"AI Output"** means any content, text, code, images, or other materials generated by LLM Providers through the Service in response to your inputs and Agent configurations. - **"AgentShelf Content"** refers to all content, templates, features, and intellectual property owned by AgentShelf, including pre-built Agent templates and marketplace offerings. - **"Team"** means a group of Users who collaborate on the Platform with shared access to Agents and Workspaces. - **"Marketplace"** means the public directory where approved Agents are listed for discovery and installation by other Users. - **"LLM Provider"** means third-party artificial intelligence service providers integrated with the Platform, including but not limited to OpenAI, Anthropic, Google, xAI, Azure OpenAI, DeepSeek, and AWS Bedrock. - **"Managed Mode"** means accessing LLM Providers through AgentShelf's platform-managed API keys, subject to usage fees and markup. - **"BYOK Mode"** (Bring Your Own Key) means accessing LLM Providers using your own API keys, without AgentShelf markup fees. - **"Subscription"** means your access tier to the Service, whether free, pro, or enterprise. --- ## 3. User Accounts ### 3.1 Account Creation and Security To use the Service, you must register for an account. You agree to: - Provide accurate, current, and complete information during the registration process - Maintain and promptly update your account information to keep it accurate and complete - Maintain the confidentiality of your account credentials, including your password and any API keys stored within the Platform - Accept responsibility for all activities that occur under your account - Notify us immediately at support@agentshelf.ai of any unauthorized use of your account or any other breach of security You must be at least 18 years of age to create an account. By creating an account, you represent that you are at least 18 years old and have the legal capacity to enter into this Agreement. ### 3.2 Account Security Measures The Platform implements the following security measures to protect your account: - Password requirements: Minimum 12 characters with complexity requirements - Account lockout: Temporary lockout after 5 failed login attempts - Session management: JWT-based authentication with token expiration - API key encryption: AES-256-GCM encryption for stored API keys (BYOK mode) **Multi-Factor Authentication (MFA):** MFA support is planned for a future release. We strongly recommend using a unique, strong password for your AgentShelf account. ### 3.3 User Responsibilities You are solely responsible for: - Your Content and conduct on the Platform - Ensuring that your use of the Service complies with all applicable laws and regulations - The security of any API keys you provide for BYOK mode - Any activities conducted by Team members you invite to your organization - Compliance with the terms of service of any LLM Providers you access through the Platform --- ## 4. License to Use the Service ### 4.1 License Grant Subject to your compliance with these Terms, AgentShelf grants you a limited, non-exclusive, non-transferable, and revocable license to access and use the Service for your personal or internal business purposes, depending on your account type. This license permits you to: - Create, configure, and deploy Agents within your account - Use Agent Workspaces for AI-assisted interactions - Collaborate with Teams and share Agents according to your Subscription tier - Access the Marketplace to discover and install publicly available Agents - Store and manage files within the Platform's storage limits ### 4.2 License Restrictions You may not: - Sublicense, sell, resell, transfer, assign, or distribute the Service or any rights therein - Modify, adapt, or create derivative works of the Service - Reverse engineer, disassemble, decompile, or otherwise attempt to derive the source code of the Service - Access the Service in order to build a competitive product or service - Use the Service in any manner that could damage, disable, overburden, or impair the Service - Circumvent or attempt to circumvent any security features or access controls - Use automated scripts, bots, or crawlers to access the Service except through our documented APIs --- ## 5. User Content & Conduct ### 5.1 Content Ownership You retain all ownership rights to the User Content you create. AgentShelf does not claim ownership over your Agent configurations, system prompts, chat histories, or uploaded files. ### 5.2 License to AgentShelf (Individual Accounts) For the purpose of operating, improving, and providing the Service, you grant AgentShelf a worldwide, non-exclusive, royalty-free license to: - Store, process, and display your Content as necessary to provide the Service - Create aggregated, anonymized statistics from usage patterns to improve platform performance and features - Use anonymized data to improve our services, algorithms, and machine learning models for the benefit of all users **Opt-Out:** If you do not want your Content used for service improvement purposes beyond providing the Service directly to you, you may opt out by contacting support@agentshelf.ai. ### 5.3 Enterprise Accounts AgentShelf offers separate Enterprise plans for business and organizational use. All Content created within a dedicated Enterprise workspace is subject to a separate Enterprise Agreement. Under our standard Enterprise Agreement: - **Your Content is considered your Confidential Information** - Your Content will **never** be used to train machine learning models - Your Content will **only** be used for providing the Service directly to your organization - Additional security, compliance, and data residency options may be available Please contact our sales team at support@agentshelf.ai for more information on our Enterprise offerings. ### 5.4 AI-Generated Output Ownership and Rights **Ownership of Output:** Subject to the rights of third parties and the terms of the applicable LLM Provider, you own the Output generated through your use of the Service to the extent permitted by applicable law. AgentShelf does not claim ownership of Output generated through your Agents. **Important Limitations on Output:** - **No Guarantee of Originality:** AI Output may be similar or identical to content generated for other users or to pre-existing content. AgentShelf makes no representation that Output is original, unique, or non-infringing. - **No Intellectual Property Warranty:** AgentShelf does not warrant that Output does not infringe upon the intellectual property rights of third parties, including copyrights, trademarks, patents, or trade secrets. The Output may inadvertently reproduce or closely resemble copyrighted material, trademarked content, or other protected works. - **LLM Provider Terms Apply:** Output is subject to the terms of service of the underlying LLM Provider. Some providers may retain rights to Output or impose restrictions on its use. You are responsible for reviewing and complying with applicable LLM Provider terms. - **No Guarantee of Accuracy:** Output may contain errors, inaccuracies, hallucinations, or misleading information. You are solely responsible for evaluating and verifying the accuracy, completeness, and appropriateness of any Output before use. **Your Responsibilities for Output:** - You are solely responsible for your use, modification, and distribution of Output - You must review Output for potential intellectual property issues before commercial use - You must not represent Output as human-created when disclosure of AI involvement is required by law or contract - You assume all risk and liability for any claims arising from your use of Output **Human Oversight Requirement:** You acknowledge that AI systems have inherent limitations and that human review and judgment are essential, particularly for: - Decisions affecting individuals' rights, employment, credit, insurance, or healthcare - Legal, financial, medical, or safety-critical applications - Content intended for publication or commercial distribution - Any use where errors could cause significant harm ### 5.5 Marketplace Submissions If you submit an Agent to the public Marketplace: - You grant AgentShelf and other Users a license to use, display, and interact with your Agent according to its published settings - You represent that your Agent does not violate any third-party rights or these Terms - AgentShelf reserves the right to review, approve, reject, or remove any Marketplace submission at our sole discretion - You retain ownership of your Agent configuration but grant a public license for its use within the Platform ### 5.5 Acceptable Use Policy You agree not to use the Service to create, upload, share, or generate any Content that: **Illegal or Harmful Content:** - Is unlawful, threatening, abusive, harassing, defamatory, libelous, or invasive of privacy - Promotes discrimination, bigotry, racism, hatred, harassment, or harm against any individual or group - Contains or promotes violence, terrorism, or illegal activities - Exploits minors in any way or contains child sexual abuse material (CSAM) **Intellectual Property Violations:** - Infringes upon any third party's intellectual property rights, including copyrights, patents, trademarks, or trade secrets - Misappropriates others' proprietary information or trade secrets - Violates any confidentiality obligations you have to third parties **Security Threats:** - Contains viruses, malware, corrupted data, or other harmful code - Attempts to circumvent security measures or gain unauthorized access - Constitutes unauthorized data collection or surveillance - Involves credential harvesting, phishing, or social engineering attacks **Deceptive Practices:** - Creates Agents that impersonate real persons or organizations without authorization - Generates misleading or deceptive content at scale - Spreads misinformation or disinformation - Manipulates or deceives users or third parties **AI-Specific Restrictions:** - Creates Agents designed to generate content that violates LLM Provider terms of service - Uses the Platform to bypass or circumvent LLM Provider safety measures - Engages in activities that could harm AI systems or their users **High-Stakes Automated Decision-Making Restrictions:** You agree **not** to use the Service for fully automated decision-making in high-stakes contexts without appropriate human oversight and compliance measures. Specifically, you must not use AI Output as the sole basis for decisions in the following areas without meaningful human review: - **Employment Decisions:** Hiring, firing, promotion, compensation, or other employment-related determinations - **Financial Decisions:** Credit scoring, loan approvals, insurance underwriting, or investment recommendations affecting individuals - **Healthcare Decisions:** Medical diagnoses, treatment recommendations, or healthcare resource allocation - **Legal Decisions:** Legal advice, case outcome predictions, or decisions affecting legal rights - **Educational Decisions:** Academic admissions, grading, disciplinary actions, or scholarship determinations - **Government Benefits:** Eligibility determinations for public benefits, housing, or social services - **Safety-Critical Systems:** Decisions affecting physical safety, infrastructure, or emergency response **If you use the Service in any high-stakes context, you represent and warrant that:** 1. You have implemented appropriate human oversight and review processes 2. You are in compliance with all applicable laws and regulations, including but not limited to the EU AI Act, state and federal anti-discrimination laws, sector-specific regulations, and professional licensing requirements 3. You have conducted appropriate risk assessments and bias audits 4. Affected individuals are informed when AI is used in decisions affecting them, as required by applicable law 5. You maintain appropriate documentation and audit trails 6. You accept full responsibility for any decisions made using AI Output **AgentShelf makes no representations regarding the suitability of the Service for high-stakes applications** and disclaims all liability for decisions made using AI Output in such contexts. We reserve the right, but not the obligation, to monitor, review, and remove any Content that we, in our sole discretion, deem to be in violation of this policy. Violation of this Acceptable Use Policy may result in immediate account termination. --- ## 6. Third-Party Services & LLM Providers ### 6.1 LLM Provider Integration The Service integrates with multiple third-party LLM Providers to power Agent interactions. Currently supported providers include: - **OpenAI** (GPT models) - **Anthropic** (Claude models) - **Google** (Gemini models) - **xAI** (Grok models) - **Azure OpenAI** (Enterprise GPT models) - **DeepSeek** (Open-source models) - **AWS Bedrock** (Multi-model service) ### 6.2 Data Transmission to LLM Providers By using the Service, you acknowledge and agree that: - Your chat messages, uploaded files, and Agent configurations may be transmitted to LLM Providers to generate responses - Data transmission is necessary for the core functionality of the Service - Each LLM Provider has its own terms of service and privacy policy that govern their handling of data - AgentShelf does not control how LLM Providers process, store, or use data transmitted to them ### 6.3 BYOK Mode Responsibilities and Liability If you use BYOK (Bring Your Own Key) mode, the following terms apply: **Your Direct Relationship with LLM Providers:** - You are directly establishing a contractual relationship with each LLM Provider - You must independently agree to and comply with each provider's terms of service - AgentShelf is not a party to your agreement with any LLM Provider **Financial Responsibility and Cost Liability:** - **You are solely and exclusively responsible for all costs, charges, and fees incurred through your API keys**, regardless of how those charges arose - This includes charges resulting from: - Normal usage through the Platform - Unauthorized access to your API keys (whether or not due to a security incident involving AgentShelf) - Misconfigured budget limits or usage controls - Team member usage under your account - Automated processes, scripts, or integrations you configure - Any errors, bugs, or unexpected behavior in the Service - **AgentShelf shall not be liable for any LLM Provider charges under any circumstances**, including charges resulting from security breaches, service errors, or unauthorized access - You are responsible for monitoring your usage and setting appropriate spending limits with your LLM Provider **API Key Security:** - AgentShelf encrypts your API keys using AES-256-GCM encryption with PBKDF2 key derivation - API keys are stored in encrypted form and only decrypted at the moment of use - Despite these security measures, **no system is completely secure** - You acknowledge and accept the inherent risks of storing API keys with a third-party service - You should regularly rotate your API keys and monitor for unauthorized usage - You must immediately notify AgentShelf and your LLM Provider if you suspect your keys have been compromised **Recommended Safeguards:** - Set spending limits and usage caps directly with your LLM Provider - Enable billing alerts with your LLM Provider - Use API keys with restricted permissions when possible - Regularly review usage logs and billing statements - Consider using separate API keys for different purposes or teams ### 6.4 Third-Party Service Disclaimer AgentShelf does not endorse, guarantee, or assume responsibility for: - The availability, accuracy, or reliability of LLM Provider services - Content generated by LLM Providers through your Agents - Any data handling practices of LLM Providers - Changes to LLM Provider pricing, capabilities, or terms Your use of third-party services through the Platform is at your own risk. --- ## 7. Intellectual Property Rights ### 7.1 AgentShelf Intellectual Property The Platform and all its original content (excluding User Content), features, and functionality are and will remain the exclusive property of AgentShelf and its licensors. This includes: - The AgentShelf name, logo, and branding - Platform architecture, design, and user interface - Proprietary algorithms and software - Documentation, templates, and AgentShelf-created content The Service is protected by copyright, trademark, trade secret, and other intellectual property laws of the United States and foreign jurisdictions. ### 7.2 Trademark Usage Our trademarks and trade dress may not be used in connection with any product or service without the prior written consent of AgentShelf. You may not use our branding to: - Suggest endorsement or affiliation without authorization - Create confusion about the source of products or services - Disparage or tarnish our trademarks ### 7.3 Feedback If you provide feedback, suggestions, or ideas about the Service ("Feedback"), you grant AgentShelf a non-exclusive, worldwide, royalty-free, perpetual license to use, incorporate, and commercialize such Feedback without compensation or attribution. --- ## 8. Fees, Payments, and Subscriptions ### 8.1 Subscription Tiers AgentShelf offers the following subscription tiers: - **Free:** Basic access with limited features and usage quotas - **Pro:** Enhanced capabilities, higher rate limits, and additional features - **Enterprise:** Advanced features, dedicated support, custom integrations, and compliance features Specific features and limitations for each tier are detailed on our pricing page and may be updated from time to time. ### 8.2 LLM Usage Fees In addition to subscription fees, you may incur charges based on your LLM usage: **Managed Mode:** - AgentShelf provides platform-managed API access to LLM Providers - A markup fee (currently 20%) is applied to LLM Provider costs - Usage is metered by tokens (input, output, and special token types) - Real-time cost tracking is available through the Platform **BYOK Mode:** - You use your own LLM Provider API keys - No AgentShelf markup is applied - You are billed directly by the LLM Provider - AgentShelf tracks usage for analytics purposes only ### 8.3 Budget Controls The Platform provides budget management features: - Set spending limits (daily, weekly, monthly, or 30-day rolling) - Configure alert thresholds (default: 85%, 95%, 100%) - Automatic request blocking when budget is exceeded - Real-time spending notifications You are responsible for configuring appropriate budget limits. AgentShelf is not responsible for charges incurred due to misconfigured budget settings. ### 8.4 Billing and Payment (Future) **Beta Period:** During the beta period, certain features may be provided free of charge or at reduced rates. Standard billing will be implemented in future releases. When billing is implemented: - Subscription fees will be billed in advance on a recurring basis - Usage fees will be calculated and billed based on your billing cycle - All fees are quoted in USD - You authorize AgentShelf to charge your payment method on file ### 8.5 No Refunds All fees are non-refundable except as required by applicable law. We do not provide refunds or credits for: - Partial subscription periods - Unused features or tokens - Account terminations - Service disruptions within our stated SLA (when applicable) In the event of a material breach of these Terms by AgentShelf, your sole remedy is to terminate your account. ### 8.6 Subscription Changes **Upgrades:** Changes take effect immediately with prorated billing. **Downgrades:** Changes take effect at the end of your current billing period. Content exceeding new tier limits may become read-only until you reduce usage or upgrade. **Cancellation:** Your account will be downgraded to Free tier at the end of your billing cycle. Content exceeding Free tier limits will become read-only. --- ## 9. Team Collaboration ### 9.1 Team Creation and Management Users may create Teams to collaborate on the Platform. The Team creator becomes the Team Owner and is responsible for: - Managing Team membership and roles - Configuring Team-level settings and permissions - Ensuring Team members comply with these Terms - Any actions taken by Team members within the Team workspace ### 9.2 Team Roles and Permissions Teams support the following roles: - **Owner:** Full administrative control, including Team deletion - **Admin:** Member management and settings configuration - **Member:** Access to shared Agents and workspace management - **Viewer:** Read-only access to shared resources ### 9.3 Agent Sharing When sharing Agents with a Team: - Each Team member receives their own isolated Workspace for the shared Agent - Chat histories and files are private to each member - Permission levels (view, edit, admin) control what members can modify - The Agent owner can revoke sharing at any time ### 9.4 Team Liability Team Owners and Administrators are jointly responsible for: - Compliance with these Terms by all Team members - Appropriate use of shared Agents and Workspaces - Managing member access and permissions appropriately - Any violations committed through Team resources --- ## 10. Marketplace ### 10.1 Marketplace Participation The AgentShelf Marketplace allows Users to: - Discover publicly available Agents - Install Agents created by other Users - Submit their own Agents for public listing - Rate and review Agents they have used ### 10.2 Submission and Review Process Agent submissions undergo a review process: 1. User submits Agent for review 2. AgentShelf reviews submission for compliance with guidelines 3. Submission is approved, rejected, or returned for modifications 4. Approved Agents are listed in the Marketplace AgentShelf reserves the right to reject, remove, or suspend any Marketplace listing at our sole discretion, with or without notice. ### 10.3 Marketplace Content Disclaimer Marketplace Agents are created by third-party Users. AgentShelf: - Does not endorse or guarantee Marketplace content - Does not verify the accuracy or quality of Agent outputs - Is not responsible for any damages arising from Marketplace Agent use - Does not guarantee continued availability of any Marketplace Agent --- ## 11. Disclaimer of Warranties THE SERVICE IS PROVIDED ON AN "AS IS" AND "AS AVAILABLE" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED. AGENTSHELF SPECIFICALLY DISCLAIMS ALL WARRANTIES, INCLUDING, BUT NOT LIMITED TO: - **MERCHANTABILITY:** No warranty that the Service is fit for commercial use - **FITNESS FOR A PARTICULAR PURPOSE:** No warranty that the Service meets your specific requirements - **NON-INFRINGEMENT:** No warranty that the Service does not infringe third-party rights - **ACCURACY:** No warranty that AI-generated content is accurate, complete, or reliable - **AVAILABILITY:** No warranty that the Service will be uninterrupted, secure, or error-free - **DATA INTEGRITY:** No warranty that your data will not be lost, corrupted, or compromised **BETA DISCLAIMER:** During the beta period, features may be incomplete, contain bugs, or be modified or discontinued without notice. Beta features are provided for testing purposes and should not be relied upon for production or mission-critical use cases. THE USE OF THE SERVICE IS AT YOUR SOLE RISK. YOU ARE SOLELY RESPONSIBLE FOR EVALUATING THE ACCURACY, COMPLETENESS, AND USEFULNESS OF ANY CONTENT GENERATED THROUGH THE SERVICE. --- ## 12. Limitation of Liability TO THE MAXIMUM EXTENT PERMITTED BY APPLICABLE LAW: **NO CONSEQUENTIAL DAMAGES:** In no event shall AgentShelf, its affiliates, officers, directors, employees, agents, or licensors be liable for any indirect, punitive, incidental, special, consequential, or exemplary damages, including, without limitation: - Loss of profits, goodwill, or business opportunities - Loss of data or Content - Business interruption - Any other intangible losses **LIABILITY CAP:** In no event shall AgentShelf's aggregate liability for all claims relating to the Service exceed the greater of: - The amount you paid to AgentShelf during the twelve (12) months prior to the event giving rise to the claim, or - One hundred dollars ($100) **AI-GENERATED CONTENT:** AgentShelf is not liable for any actions taken based on AI-generated content, including decisions made using Agent outputs or recommendations. **THIRD-PARTY SERVICES:** AgentShelf is not liable for any damages arising from your use of LLM Providers or other third-party services integrated with the Platform. THE FOREGOING LIMITATIONS WILL APPLY WHETHER OR NOT AGENTSHELF HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES AND REGARDLESS OF THE THEORY OF LIABILITY. --- ## 13. Indemnification ### 13.1 General Indemnification You agree to indemnify, defend, and hold harmless AgentShelf, its officers, directors, employees, agents, affiliates, and licensors from and against any and all claims, liabilities, damages, losses, costs, and expenses (including reasonable attorneys' fees) arising out of or in any way connected with: - Your access to or use of the Service - Your User Content, including Agent configurations and chat interactions - Your violation of these Terms - Your violation of any third-party rights, including intellectual property rights - Your violation of any applicable laws or regulations - Actions taken by Team members you have invited or manage - Your use of LLM Providers through the Platform ### 13.2 AI Output Indemnification **You specifically agree to indemnify, defend, and hold harmless AgentShelf** from and against any and all claims, liabilities, damages, losses, costs, and expenses (including reasonable attorneys' fees) arising out of or in any way connected with: - **Intellectual Property Claims:** Any claim that Output generated through your use of the Service infringes, misappropriates, or violates any third party's intellectual property rights, including copyrights, trademarks, patents, trade secrets, or rights of publicity - **Content Claims:** Any claim arising from the content, accuracy, or nature of Output, including claims of defamation, invasion of privacy, or violation of any law or regulation - **Use of Output:** Your use, modification, distribution, publication, or commercialization of Output - **Downstream Liability:** Any claims by third parties to whom you have provided, sold, licensed, or distributed Output - **Regulatory Violations:** Any claims arising from your use of Output in violation of applicable laws, regulations, or industry standards, including data protection, consumer protection, or sector-specific regulations - **Misrepresentation:** Any claims arising from your failure to disclose that content was AI-generated when such disclosure was required by law, regulation, contract, or professional standards ### 13.3 Indemnification Procedures AgentShelf will: - Provide you with prompt written notice of any claim subject to indemnification - Allow you to control the defense and settlement of the claim (provided that you may not settle any claim that admits liability on behalf of AgentShelf or imposes obligations on AgentShelf without our prior written consent) - Provide reasonable cooperation in the defense of the claim at your expense ### 13.4 Survival This indemnification obligation will survive the termination of this Agreement and your use of the Service. --- ## 14. Governing Law & Dispute Resolution ### 14.1 Governing Law This Agreement and any disputes arising out of or related to it will be governed by the laws of the State of Wyoming, USA, without regard to its conflict of law provisions. ### 14.2 Binding Arbitration Any dispute, controversy, or claim arising out of or relating to this Agreement, or the breach thereof, shall be settled by final and binding arbitration administered by the American Arbitration Association ("AAA") in accordance with its Commercial Arbitration Rules. The arbitration shall be conducted in Wyoming, USA. The arbitration award may be entered as a judgment in any court of competent jurisdiction. The arbitrator shall have authority to award any remedy or relief available under applicable law. ### 14.3 Waiver of Class Action and Jury Trial **YOU AND AGENTSHELF AGREE THAT EACH MAY BRING CLAIMS AGAINST THE OTHER ONLY IN YOUR OR ITS INDIVIDUAL CAPACITY AND NOT AS A PLAINTIFF OR CLASS MEMBER IN ANY PURPORTED CLASS OR REPRESENTATIVE PROCEEDING.** By agreeing to these Terms, you are waiving your right to: - Participate in a class-action lawsuit - Participate in class-wide arbitration - Trial by jury ### 14.4 Exceptions to Arbitration Notwithstanding the above, either party may seek: - Injunctive or other equitable relief in any court of competent jurisdiction to prevent actual or threatened infringement of intellectual property rights - Resolution of disputes in small claims court for claims within that court's jurisdiction --- ## 15. Termination ### 15.1 Termination by AgentShelf We may terminate or suspend your account and access to the Service immediately, without prior notice or liability, for any reason, including but not limited to: - Breach of these Terms - Violation of the Acceptable Use Policy - Non-payment of applicable fees - Fraudulent or illegal activity - Extended periods of inactivity - Legal or regulatory requirements - Risk to the security or integrity of the Service ### 15.2 Termination by You You may terminate your account at any time by: 1. Contacting us at support@agentshelf.ai 2. Using the account deletion feature in your account settings (when available) Upon requesting termination, your account will be scheduled for deletion. ### 15.3 Effect of Termination Upon termination: - Your license to use the Service immediately ceases - Your access to your account and Content will be revoked - Your Content will be deleted in accordance with our Privacy Policy and data retention practices - Team Workspaces you own will be affected (members will lose access) - Marketplace Agents you published may be removed **Data Export:** We recommend exporting any Content you wish to retain before terminating your account. A data export feature is planned for a future release. Please ensure you have saved all necessary Content before initiating account termination. ### 15.4 Survival All provisions of these Terms which, by their nature, should survive termination shall survive, including but not limited to: - Ownership provisions - Warranty disclaimers - Indemnification obligations - Limitations of liability - Dispute resolution provisions --- ## 16. Changes to the Terms We reserve the right, at our sole discretion, to modify or replace these Terms at any time. ### 16.1 Definition of Material Changes A change to these Terms is considered **"material"** if it: - **Modifies your rights:** Reduces your rights or increases your obligations under these Terms - **Changes pricing:** Introduces new fees, increases existing fees, or changes billing practices - **Affects data usage:** Expands how we may use your Content or data - **Modifies liability:** Changes limitations of liability or indemnification obligations - **Alters dispute resolution:** Changes the governing law, arbitration requirements, or class action waiver - **Changes acceptable use:** Significantly modifies the Acceptable Use Policy - **Affects intellectual property:** Changes ownership rights to User Content or Output - **Modifies BYOK terms:** Changes your responsibilities or liability for BYOK mode usage ### 16.2 Notification of Changes **For Material Changes:** - We will provide at least **30 days' advance notice** before material changes take effect - Notice will be sent via email to your registered email address - A prominent banner or notification will be displayed within the Platform - For significant changes, we may require affirmative acceptance before continued use **For Non-Material Changes:** - We will update the "Last Updated" date at the top of this document - Changes will be posted on our website - We encourage you to review periodically ### 16.3 Acceptance By continuing to access or use the Service after material changes become effective, you agree to be bound by the revised Terms. If you do not agree to the revised Terms, you must stop using the Service and may terminate your account before the changes take effect. ### 16.4 Access to Previous Versions Upon request, we will provide you with previous versions of these Terms. Contact support@agentshelf.ai. ### 16.5 Review Recommendation We encourage you to review these Terms periodically for any changes. The "Last Updated" date at the top of this document indicates when the Terms were last revised. --- ## 17. Beta Program Terms ### 17.1 Beta Features Certain features of the Service may be designated as "Beta," "Preview," "Early Access," or similar designations. These features: - Are provided for evaluation and testing purposes - May be incomplete, contain bugs, or be unstable - May be modified, suspended, or discontinued at any time without notice - Should not be used for production or mission-critical purposes ### 17.2 Beta Feedback By participating in the beta program, you agree to: - Provide feedback and bug reports when requested - Not publicly disclose beta features without AgentShelf's consent - Understand that beta features may not be released in final form ### 17.3 Planned Features The following features are planned for future releases (subject to change): - Multi-factor authentication (MFA) - Data export functionality - Enhanced file processing and virus scanning - Advanced analytics and reporting - Payment processing integration - Email notifications for Team invitations and alerts - API versioning These planned features are not guaranteed and may be modified, delayed, or cancelled. --- ## 18. General Provisions ### 18.1 Severability If any provision of this Agreement is held to be invalid, illegal, or unenforceable, that provision will be limited or eliminated to the minimum extent necessary, and the remaining provisions of these Terms will remain in full force and effect. ### 18.2 Waiver The failure of AgentShelf to enforce any right or provision of these Terms will not be considered a waiver of those rights. Any waiver must be in writing and signed by AgentShelf to be effective. ### 18.3 Entire Agreement These Terms, along with our Privacy Policy and any applicable Enterprise Agreement, constitute the entire agreement between you and AgentShelf regarding the Service and supersede all prior agreements, understandings, and communications. ### 18.4 Assignment You may not assign or transfer these Terms or your rights hereunder without AgentShelf's prior written consent. AgentShelf may assign these Terms without restriction. ### 18.5 Force Majeure AgentShelf shall not be liable for any failure or delay in performance due to circumstances beyond our reasonable control, including but not limited to acts of God, natural disasters, war, terrorism, labor disputes, government actions, internet or telecommunications failures, or third-party service outages. ### 18.6 Notices Notices to AgentShelf should be sent to: - **Email:** support@agentshelf.ai - **Address:** Talavera Solutions LLC, [Address to be provided] Notices to you will be sent to the email address associated with your account. ### 18.7 Relationship of Parties Nothing in these Terms creates a partnership, joint venture, employment, or agency relationship between you and AgentShelf. You have no authority to bind AgentShelf in any manner. --- ## 19. Contact Information If you have any questions about these Terms, please contact us at: **Talavera Solutions LLC** d/b/a AgentShelf.ai - **General Support:** support@agentshelf.ai - **Legal Inquiries:** support@agentshelf.ai - **Enterprise Sales:** support@agentshelf.ai - **Security Issues:** support@agentshelf.ai --- ## 20. Acknowledgment BY CREATING AN ACCOUNT OR USING THE SERVICE, YOU ACKNOWLEDGE THAT YOU HAVE READ, UNDERSTOOD, AND AGREE TO BE BOUND BY THESE TERMS OF SERVICE AND OUR PRIVACY POLICY. --- **Version:** 1.1.0 (Beta) **Effective Date:** December 2, 2025 **Document Owner:** Talavera Solutions LLC