One control plane for every AI agent
Observability, governance, and guardrails for autonomous agentsPrismor intercepts every tool call your agents make, enforces policy, and keeps a full audit trail
What is an AI agent control plane?
As AI agents move from writing code to running it — opening pull requests, calling APIs, touching production — the risk moves with them. A prompt is easy to change; a tool call is where an agent actually does something. That boundary is where control belongs.
An AI agent control plane sits between your agents and everything they can reach. It watches every tool call, decides whether policy allows it, applies guardrails in real time, and records the outcome. The result is a single place to see what your agents are doing, govern what they’re allowed to do, and prove it later.
Five layers, one boundary
Everything Prismor enforces at the tool call your agents share
AI Agent Observability
See every tool call, file read, shell command, and network request your agents make — as it happens, not after an incident. Telemetry is structured and searchable, with secrets redacted before anything leaves the machine.
- Per-tool-call event stream
- Secrets redacted at the source
- Searchable across every agent and repo
AI Agent Governance & Policy
Write policy once and enforce it everywhere. Signed policies define what each agent may touch — which tools, which paths, which hosts — and push to every enrolled agent so governance is consistent, versioned, and reviewable.
- Centrally authored, cryptographically signed policy
- Allow / deny per tool and per resource
- Versioned and auditable changes
AI Agent Guardrails
Stop dangerous actions before they run. Prismor evaluates each tool call against policy in real time and blocks destructive commands, secret exfiltration, and off-limits paths. When something breaks or a policy can’t be verified, it fails closed.
- Real-time block on risky actions
- Blocks secret leakage and destructive commands
- Fail-closed by default
AI Agent Identity & Access
Give every agent a cryptographic identity instead of a shared key. Agents enrol with their own credential, get exactly the access their policy grants — least privilege, zero standing access — and can be revoked the instant something looks wrong.
- Per-agent cryptographic enrolment
- Least privilege and zero standing access
- Instant revocation
Monitoring & Audit Trail
Keep a tamper-evident record of everything your agents did — who, what, when, and whether it was allowed or blocked. Monitor activity live and export the trail when auditors, security reviews, or an incident come calling.
- Tamper-evident action log
- Live activity monitoring
- Export for audit and compliance
Tool-Call & MCP Interception
The control plane sits at the boundary every agent shares: the tool call. That includes Model Context Protocol servers, so a governed MCP connection carries the same policy, guardrails, and audit trail as everything else the agent does.
- Enforcement at the tool-call boundary
- Governed MCP servers
- Works with the major AI agents
Frequently asked questions
What is an AI agent control plane?
An AI agent control plane is the layer that sits between your AI agents and everything they can act on. It intercepts each tool call, decides whether policy allows it, applies guardrails, and records the result — giving you observability, governance, and control over autonomous agents from one place.
How do you get observability into what AI agents are doing?
Prismor captures every tool call, command, file access, and network request an agent makes as a structured, searchable event stream, with secrets redacted at the source. You see agent activity as it happens instead of reconstructing it after an incident.
How is this different from prompt-based guardrails?
Prompt-based guardrails try to steer the model with instructions the model can ignore or be tricked past. Prismor enforces at the tool-call boundary — the point where an agent actually does something — so a blocked action never runs, regardless of what the prompt said.
Which AI agents and MCP servers does Prismor work with?
Prismor governs agents at the tool-call layer they share, including Model Context Protocol servers, so it works across the major AI coding agents and agent frameworks rather than being tied to one vendor.
Want a control plane over your AI agents?
Prismor can set this up across your whole org — continuous scanning, SBOM/VEX generation, auto-remediation, and audit-ready CRA compliance. Tell us your stack and we’ll take it from here.