Use cases
Where AI agents slip past today’s controls.
Agents enter production with valid credentials and broad access. These are the moments where identity and security tools stop, and where Watchlight AI Beacon clears, grounds and records every governed action.
Where enterprises start
Three problems Watchlight solves first
Prevent unauthorized agent actions
Prevent agents from acting outside their authority.
An authenticated agent is not necessarily authorized to take every action available to it. Watchlight evaluates delegated authority and policy before execution, preventing actions that exceed the boundaries of an approved task.
- Deterministic pre-action authorization
- Intent-aware policy evaluation
- Delegation chain validation
- Strict-subset authority attenuation
Control autonomous multi-agent workflows
Keep delegated authority under control.
As agents delegate work to other agents, Watchlight enforces authority boundaries throughout the execution lifecycle, detects violations, and provides mechanisms to contain unsafe behavior.
- Delegation chain enforcement
- Runtime drift detection
- Agent quarantine
- Delegation subtree containment
- Authority revocation
Prove AI agent accountability
Know what happened, who authorized it, and why.
Watchlight preserves signed, tamper-evident execution lineage connecting actions to their governing policies, delegated authority, and execution context.
- Signed execution lineage
- Policy decision evidence
- Delegation history
- Incident reconstruction
- Audit support
All scenarios
Every scenario, on the flight path.
Each one is happening in enterprises today. Each maps to the step of Agent Runtime Governance that answers it.
01Decide
The flight plan
Before takeoff, each agent gets a pre-flight manifest: what it is cleared to do, and on whose authority.
When You Don't Know What AI Agents Are Already Running
AI agents and MCP servers are stood up faster than anyone can track. You cannot govern, or even see, the agents and infrastructure you do not know exist.
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When AI Agents Hold More Access Than They Need
Agents often run with broad, always-on access they rarely use. Access should be given only when needed, and taken away when the task is done.
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02Enforce
Radar
Each governed action is checked against that plan before it runs, step by step, in real time.
When an AI Agent Does More Than You Asked
You ask an agent to do one thing. It decides to do more. The permission was valid, but the action was never what you intended.
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When an AI Agent Runs a Whole Process on Its Own
An agent logs in once, then takes hundreds of actions across your systems. Nothing checks whether each one is actually the right thing to do.
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When One AI Agent Hands Work to Another
Agents pass tasks to other agents. With each handoff, access can quietly grow, until an agent can reach far more than anyone intended.
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03Contain
Grounding
The moment an agent goes off course, Beacon stops it, quarantines it, or revokes its clearance.
When an AI Agent Goes Wrong While It Is Still Running
An agent starts behaving differently partway through a task. Its permissions are still valid, and denying the next call does not reach the work already in flight.
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When AI Agents Remember Sensitive Data
Agents remember what they have seen. Customer or confidential data from one task can resurface in another, where it does not belong.
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04Prove
The black box
A hash-chained, tamper-evident record of the whole flight, from clearance to landing.
When You Can't Prove What an AI Agent Did
When something goes wrong, ordinary logs cannot tell you who allowed the action or why. You need a record you can actually stand behind.
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Take the next step
Recognize these gaps in your organization?
See Watchlight AI Beacon decide, enforce, contain and prove agent actions on a real run, or start with an advisory workshop to map where your gaps are.