One identity across tools
Keep the agent's business identity connected even when models, harnesses, or runtimes change.
Operating model
Talk to a human AI agent management and registry
Manage every agent as part of the workforce.
Grid creates one living registry for the agents teams bring to work—who owns them, where they run, what they touch, and whether they still belong.
GridAgent registryLive record
- Agent
- Finance Ops Agent Active
- Owner
- Nina Patel · Finance Current
- Runtime
- Managed harness · v3 Tracked
- Lifecycle
- Review due in 4 days Review
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What the registry must hold
An inventory should explain the agent, not just name it.
A useful AI agent registry stays connected to the work. It shows why an agent exists, who is responsible, what changed, which systems are involved, and when the next decision is due.
A lifecycle, not a launch list
Track proposed, testing, active, paused, review, and retired states with a clear decision owner.
Context every function can use
Give security, finance, operations, and business teams the same current operating record.
The operating loop
Keep the registry current as the workforce changes.
Grid connects discovery, ownership, access, activity, cost, and outcomes so the agent inventory can support real decisions.
- 01
Discover
Find agents across approved tools, private runtimes, and team workflows.
- 02
Register
Attach an owner, purpose, environment, and operating scope.
- 03
Maintain
Update the record as access, versions, activity, and cost change.
- 04
Retire
Remove access and preserve the operating history when work ends.
Evidence for the operating model
Start with the field notes behind the work.
Our notes separate what has been observed from what teams should test next.
Common questions
What teams need to know.
01What is AI agent management?
AI agent management is the ongoing work of discovering, registering, assigning, reviewing, and retiring agents across an organization. It keeps technical configuration connected to business ownership and purpose.
02What belongs in an AI agent registry?
A practical registry includes identity, owner, business purpose, model and harness, runtime, systems, permissions, lifecycle state, cost, recent activity, review dates, and expected outcomes.
03How do companies keep an AI agent inventory current?
Combine automated discovery and system integrations with owner attestations, change history, lifecycle states, and scheduled reviews. A static spreadsheet becomes stale because it is separated from the activity it describes.
Start with who is already at work
Give every agent a place in the operating model.
Map the agents, owners, access, activity, cost, and outcomes already taking shape across the company.