Monitor your AI agents in real time
AI agent monitoring watches what your agents do as they do it, surfacing risky actions the moment they happen and keeping a permanent record you can go back to.
AI agent monitoring is the continuous tracking of agent activity for security, reliability, and compliance. Observability makes agent actions visible. Monitoring watches them over time: spotting anomalies, enforcing limits, keeping evidence.
For teams running agents against production systems, monitoring is the gap between catching a bad action in the moment and finding it weeks later in a post-mortem.
What to monitor across your agents
Good AI agent monitoring watches the signals that actually indicate trouble:
- Blocked and denied actions, attempts to do something policy forbids.
- Sensitive operations touching secrets, credentials, or protected paths.
- Unusual volume or patterns of tool calls from a single agent.
- Policy changes, and who made them.
A tamper-evident audit trail
Monitoring is only as trustworthy as its record. Prismor keeps a tamper-evident audit trail of every action an agent took: who, what, when, allowed or blocked, so the history can't be quietly rewritten.
That trail turns "what did our agents do last quarter?" from a guess into an answer you can export for auditors and security reviews.
Monitoring that can act, not just watch
Prismor sits inline at the tool-call boundary, so monitoring isn't passive. The same layer that records an action can block it, require approval, or fail closed. A dangerous action gets stopped, not just logged after the fact.
Frequently asked questions
What is AI agent monitoring?
The continuous tracking of what AI agents do at runtime, their tool calls and system operations, to surface risky behavior in real time and keep an auditable record.
What's the difference between monitoring and observability for AI agents?
Observability is the capability to see agent actions. Monitoring is watching those actions over time, alerting on anomalies, and retaining an audit trail.