AI Agent Governance
Give AI agents scoped access to your compliance data
Expose your full GRC lifecycle to Claude, Cursor, and custom LLM agents via native Model Context Protocol (MCP) tools.
What changes
Drafting policies by hand takes weeks of legal back-and-forth
AI agents draft contextual security policies directly mapped to ISO 27001, SOC 2, and NIST controls, ready for human review.
Engineers spend hours taking screenshots for auditors
LLM agents query telemetry APIs and assemble structured evidence packs automatically with source attribution.
Engineering teams adopt LLMs without governance oversight
Continuous inventory and policy checks for internal model deployments, API token exposures, and prompt logging practices.
AI outputs cannot be trusted blindly in regulatory audits
Agent actions that change state wait for a human approval, and every agent action and sign-off is written to the audit log.
What's included
Native MCP tools
Read, assess, and update compliance resources directly from any MCP-compatible agent.
Use it from your editor
Query control status and submit evidence directly inside developer workflows.
Human approval first
Require a named reviewer before any AI-drafted policy or risk change goes live.
An audit trail for agents
The event log records the request, the agent identity, and the person who approved it.
Related capabilities
Compliance automation
Map once, prove everywhere
Evidence collection
Proof with its source attached
Continuous monitoring
Catch drift as it happens
Find out what your compliance program actually looks like
Thirty minutes, your real systems, no slideware. We'll show you what we'd automate first, and what you don't need us for.