Every new agent is a new blind spot
Agents connect to internal tools, APIs, and data across teams. Full governance is the only way to catch unauthorized actions and shadow agents before they become incidents.
By business need
Govern every agent, not just the ones you know about.
Autonomous agents now read your documents, call your APIs, and take actions across departments. Governance means you can answer, for any agent at any time: who owns it, what it's allowed to touch, and what it actually did.
Why it matters
Ungoverned agents are the blind spot you inherit by default
Autonomy without accountability is a liability
An agent that can act without a traceable owner and a defined scope is a liability the moment something goes wrong-not because of malice, but because of scope creep.
Compliance now demands auditability
Frameworks like the EU AI Act, NIST AI RMF, and ISO 42001 require organizations to demonstrate control over AI systems, not just describe good intentions.
What Lineation does
One governance layer, four capabilities
Agent inventory & shadow AI discovery
Auto-discover every agent across your providers, including the ones built in Zapier, Lindy, or a script nobody documented.
Zero-trust agent identity
Every agent gets a verifiable non-human identity scoped to owner, data, and capability-never a shared service account.
Policy-as-code enforcement
Define what each agent may read, write, and never touch. Evaluated at runtime, before the action executes, not after.
Audit-ready lineage
Every decision leaves a chain: prompt → tool → data → policy → outcome. Query, export, and replay it on demand.
How it works
From unknown agents to governed ones
Discover every agent
Read-only connectors populate a full agent registry, sanctioned and unsanctioned, within minutes.
Assign scoped identity
Each agent is issued a non-human identity tied to an owner and an explicit capability set.
Enforce policy at runtime
High-risk actions are evaluated against policy before they execute, with default-deny for anything undefined.
Score risk continuously
Agent behavior is compared against its own baseline, flagging drift the moment it happens.
Produce audit-ready evidence
Every policy decision and outcome is logged immutably, ready to export for review.
FAQ
Common questions
What is AI agent governance?
Discovering every autonomous agent in your organization, assigning it a scoped identity, enforcing policy on what it may do, and keeping a lineage record of what it actually did.
Why do enterprises need it?
Agents access internal APIs, databases, and tools across departments. Without governance, security and compliance teams inherit blind spots regulators increasingly expect them to have closed.
How is this different from traditional IAM?
Traditional IAM assumes a human or static service account. Agent governance assumes a non-human identity, scoped to owner and capability, re-evaluated at every action-not once at login.
What does shadow AI have to do with governance?
You cannot govern what you cannot see. Shadow AI built outside official tooling is the most common governance gap, which is why discovery comes first.
How fast can we get visibility?
Read-only connectors typically populate a registry and activity feed within minutes, with no code changes. Enforcement is opt-in afterward.
Does governance slow agents down?
Policy runs against a locally cached set at the endpoint, so the happy path sees negligible latency-only violating actions are interrupted.
Govern the agents you have today.
Not the ones on a roadmap slide. Discover, identify, and enforce policy in one afternoon.