Infrastructure for mixed LLM providers
Connect configured models, approved knowledge, and tools through managed services and supported runtime paths.
Explore LLM infrastructureFor organizational AI adoption
Plan AI agent adoption across your organization
An enterprise AI agent platform with access to multiple LLM providers, monetary budgets, and organization and team libraries. Start with a focused workflow, then plan evaluation and onboarding with our team.
Built by operators from Axos Bank, Google, Bank of America, Comcast Voice AI
Already have a repeatable team workflow in mind? Explore a focused page about making team expertise reusable. Explore reusable team workflows
The problem
AI works for individuals. Organizations can't scale it.
LLMs can do everything. Which is why most organizations can't do anything with them.
Theoretical capabilityEnterprise adoption
Customer Support
Sales & Marketing
Operations
Finance & Legal
Product & Engineering
HR & Recruiting
Why the gap?
Nobody can build what they need
Teams can't turn their specific workflow into a tool. The capability is there. The last mile isn't.
What works can't scale
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 AI fills the vacuum
When approved paths are unclear, employees choose disconnected tools and personal accounts. Without visible ownership and usage records, adoption becomes difficult to manage.
A common enterprise adoption pattern
The gap isn't intelligence.
It's infrastructure.
Why existing tools fail
Every AI platform forces a tradeoff. AgentShelf doesn't.
Three categories. Three traps. One way out.
Easy + PowerfulNot Open
The lock-in trap
Anthropic • OpenAI • Microsoft • Salesforce
Fast to adopt, but changing models or operating environments can require rebuilding around a different stack.
Easy + OpenNot Powerful
The basic-interface trap
Lightweight AI interfaces
Easy to start, but limited when an agent needs approved tools, knowledge, files, and durable operating context.
Powerful + OpenNot Easy
The do-it-yourself trap
Developer tools and custom infrastructure
Flexible, but the organization must assemble and maintain the workspace, integrations, access rules, and deployment path.
AgentShelf addresses all three with one managed foundation
Open
Choice without hardwiring
Keep the agent’s purpose and workspace context distinct from any one supported model or deployment surface.
Powerful
A workspace for real work
Each individual agent gets a dedicated environment for approved tools, knowledge, files, and operating context.
Easy
Start with a focused agent
Begin with one user, one individual agent, and one dedicated workspace—without making custom infrastructure the first step.
One user. One focused agent. One dedicated place to work.
The dedicated workspace is where one user manages the agent’s context, tools, conversations, results, and available activity.
Platform foundation
A shared foundation for AI agent adoption
Budgets your organization sets
Admins choose soft or hard monetary budgets for organization, team, user, and widget scopes. Covered requests continue with a warning or are rejected at the applicable limit.
Explore budget controlsOrganization and team libraries
Anyone can submit agents. Organization or team managers vet and approve them. Organization agents are available across the organization; team agents are available only to team members.
Explore the Agent LibraryBoundaries and human review
Keep private workspaces separate from public or embedded agent sessions, scope access to the experience, and review available activity, usage, errors, and results with the owner.
Explore trust boundariesUse cases
Real decisions your team faces every week.
Each one used to take 30 minutes of searching and copy-pasting. Now it's a conversation.
Knowledge
Tribal knowledge, on demand
"What's our process for handling enterprise procurement?"
Search shared docs→Pull playbook sections→Cite sources→Answer in seconds
Sales
Meeting prep in seconds
"I have a call with Acme in 20 minutes."
Pull account context→Draft talking points→Reference last meeting notes→Share with team
Support
Ticket resolution from your docs
"Customer says their integration broke after the update."
Search knowledge base→Match known issue→Draft response→Escalate if needed
Governance approach
Designed for accountable AI adoption.
Keep ownership, configured access, activity, and usage visible while your organization applies its own security and compliance requirements.
Configured model access
Use approved model access and keep agent instructions and workspace context managed separately from a single provider where supported.
Activity and usage records
Review available agent activity, user interaction, and cost records with timestamps and attribution where reporting is enabled.
Clear ownership and review
Keep the user, individual agent, dedicated workspace, and configured policies connected in one reviewable relationship.
Questions about adopting AgentShelf
AgentShelf is for organizations giving non-technical teams focused AI agents. Each user works with an individual agent in its dedicated workspace for approved knowledge, tools, and operating context.
The intended starting point is guided, no-code setup around a focused use case. Technical teams can extend supported integrations when a workflow requires them.
Share the CRM, knowledge source, or business system your workflow depends on during evaluation so the team can confirm support and what setup would involve.
Agent setup includes defining behavior, limits, and human review points. During evaluation, map which decisions a person should review in your workflow.
You define the approved knowledge, tools, and operating context for an agent's workspace. Discuss your retention, deletion, and data-location requirements during evaluation.
Start with one focused job, one user, one agent, and its dedicated workspace. Hands-on onboarding scopes workspace configuration, integrations, and governance needs.
Choose one workflow to evaluate first.
Request early access to discuss a focused use case. For adoption across several teams, contact sales to discuss organizational fit and onboarding.