Agents are built faster than they're tracked
Teams spin up autonomous agents with frameworks and APIs directly - no security review requested, no entry in any inventory.
By usage
Every autonomous agent your teams built - inventoried, not invisible.
LangChain agents, AutoGPT-style loops, custom orchestration built over a weekend - autonomous agents get built faster than anyone tracks them. Each one plans, decides, and calls tools on its own, with no human checkpoint in between.
Why it matters
Autonomy without inventory is just exposure
Autonomy means no one approves each action
Unlike a human-in-the-loop tool, an autonomous agent decides and acts on its own, chaining tool calls without a checkpoint.
One compromised agent can cascade
A single hijacked or misconfigured agent with broad tool access becomes an unbounded liability, fast.
What Lineation does
Discovery first, then identity, policy, and lineage
Auto-discover every agent
Agents are discovered from LLM gateway traffic, API keys, and MCP connections - not from a spreadsheet someone forgot to update.
Scoped, zero-trust identity per agent
Each agent gets its own credential and permission boundary, replacing shared service-account keys.
Default-deny policy on every tool call
Actions outside approved scope are blocked before they execute, not flagged after the fact.
Replayable action history
Every decision and tool call is logged in order, so a surprising outcome traces back to its root cause.
How it works
Five steps to a governed agent fleet
Connect the gateway
Route agent traffic - LLM calls and tool calls - through the Lineation gateway with no code rewrite.
Auto-discover agents
Every distinct agent identity surfaces in the inventory automatically from observed traffic patterns.
Assign scoped identity
Each agent receives its own credential, tied to a defined tool and data boundary.
Enforce policy at runtime
Default-deny rules block out-of-scope actions live, not in a postmortem.
Review the trail
A replayable lineage record supports incident review and ongoing policy tuning.
FAQ
Common questions
What counts as an 'agentic AI' for this page?
Any autonomous system that plans, decides, and calls tools on its own - LangChain agents, AutoGPT-style loops, custom orchestration built in-house - not just a named vendor product.
How do you discover agents we didn't know existed?
Agents surface from LLM gateway traffic, API key usage, and MCP connections, so an agent built without a security review still shows up in the inventory.
Does this require rewriting our agent code?
No. Traffic is routed through the gateway at the network layer; the agent's own code and framework are unchanged.
What happens when an agent tries something outside policy?
The call is blocked by default-deny policy before it executes, and the attempt is logged for review.
Can we start in observe-only mode?
Yes. Observe-only mode builds the inventory and shows what agents are already doing before any policy is enforced.
How is this different from the Agentic Workflow use case?
This page covers individual autonomous agents acting on their own; Agentic Workflow covers multi-step processes that chain several agents and tools together end-to-end.
Related use cases
Keep exploring
See every agent your teams already built.
Start in observe-only mode. Turn on enforcement when you're ready.