AI SAFETY · OPERATIONAL, TESTABLE, BOUNDED

Before an AI can act, make the authority path safe.

For agents, MCP tools, automations, and AI-enabled workflows that can publish, spend, change systems, call tools, or influence real operations. We map concrete failure modes, tighten the boundaries, and return fixes you can test.

What we review

Prompt injection and untrusted-input boundaries.
Secrets, permissions, least authority, and approval gates.
Tool calls and external actions that must fail closed.
Money, publishing, infrastructure, and other high-authority paths.
Receipts, auditability, stale truth, rollback, and kill switches.
AI-generated changes that look correct but are operationally wrong.

What you receive

A threat and failure-mode map for one named workflow.
Prioritized findings tied to actual authority and consequence.
Paste-ready policy, code, config, or test artifacts where feasible.
A verification plan naming deterministic checks for each admitted fix.
A closeout receipt stating what was reviewed, repaired, and left unresolved.

THE REVIEW

Trace the AI from input to tool to consequence.
Mark where untrusted text or excessive authority enters.
Design the smallest fail-closed repair.
Prove the repair with deterministic checks and a receipt.

Not a vague “AI is safe” certificate.

This is operational safety engineering, not frontier-model alignment research, legal/compliance certification, penetration testing, or a guarantee that incidents cannot occur. Production credentials and client secrets are not requested by default.

REQUEST A REVIEW

Before an AI can act, make the authority path safe.

What we review

What you receive

Not a vague “AI is safe” certificate.

Give us one workflow with a real consequence.