AI Safety Audit
Build safe-by-design
Know from day one what you'll need to prove, and how to test it.
Step 1
Your use case, understood in a few questions
Share what you already have, a brief or a policy: the copilot reads it and only asks what's missing.
What you gain
An evaluation tailored to your use case, from the start.
Step 2
All your teams, one risk analysis
Legal, compliance, engineering, product: each team adds what it knows, and everyone works from the same published analysis.
What you gain
A shared view of risk, current at every change.
Step 3
Your coding agent builds with your risk context
Through the Mankinds MCP server, Claude Code, Codex or Cursor read the requirements of your published risk analysis while they plan and write the code.
What you gain
Requirements reach the code as it's written, not after the audit.
The questions we get asked
Does an AI choose the applicable texts?
The selection of texts and requirements is deterministic: every requirement traces back to a real source.
Are our internal policies taken into account?
Yes: their forbidden behaviors and expected controls become test targets.
When can we start?
From the design stage: the risk analysis starts from a description of the use case and the documents you already have, before the first line of code.
Which coding agents can read the risk analysis?
Claude Code, Codex, Cursor and any agent that speaks MCP. Each developer connects it once to the Mankinds MCP server, with their own account.
Who decides in the end?
Your teams. Mankinds tells you what applies and recommends how to meet it; its recommendations never state or deny compliance.
Do you inventory our AI use?
You choose the systems to evaluate; automatic inventory of AI use belongs to your governance platform.