Cost governance
Control AI usage before it becomes invisible operating spend.
AgentShelf gives operators one managed layer for model access, configured budget policies, usage records, cost reporting, and value attribution across agent workflows.
Governance & AI economics
Value attribution — spend tied to each workflow
Cross-cutting controls
Keep the agent’s owner, usage, limits, records, and boundaries in view.
These controls follow the workflow from configuration through the dedicated workspace to each supported experience. Exact behavior varies by the configured path.
Ownership & Access
Keep the responsible user, agent, workspace, and deployed experience clear, with access configured for that path.
Usage & Cost
Review available model, agent, workspace, and experience-level usage and cost information.
Budgets & Limits
Configure warnings and limits where supported. Review enforcement behavior for the experience being deployed.
Activity Records
Review available events, errors, usage, and operating records for the configured workflow.
Public / Private Boundaries
Keep authenticated controls distinct from public or embedded agent sessions.
Request path
Each request passes through policy, gateway, and records.
Instead of scattered prompts and disconnected provider bills, AgentShelf gives operators a visible path from request to provider response to usage record.
- 01
Agent request
A user or embedded surface starts a governed agent workflow.
- 02
Policy check
Configured workspace, budget, and access rules can be evaluated before model use.
- 03
LLM gateway
Approved provider and model access routes through one layer.
- 04
Usage record
Cost, model, user, individual agent, workspace, and workflow context are recorded where available.
Workflow attribution
Make AI spend explainable to finance, operations, and platform teams.
Finance
Review usage with budget context instead of reconciling disconnected provider charges.
Operations
See which workflows are adopting AI and where policy needs adjustment.
Platform teams
Govern providers, models, runtime surfaces, and shared agent infrastructure.
Responsible rollout note Budget policies and usage records support governance. Availability and enforcement behavior depend on configuration, integration scope, and the operating policies applied by each organization.
Put AI cost governance in the control plane.
See how AgentShelf can make model access, budgets, usage records, and workflow attribution part of your agent rollout from the beginning.