See it. Stop the bad stuff. Prove every decision. Proof builds itself.
The Problem
Your AI is in production. It handles real decisions for real people. But when someone asks what it did last Tuesday at 2:14 PM and whether that was within policy — you don't have an answer. You have logs. Logs are not evidence.
Every security questionnaire, every audit, every regulatory inquiry comes down to the same question: can you prove it?
Not "do you monitor it." Not "do you have dashboards." Can you produce a cryptographic, tamper-evident record of what your AI did and whether it stayed in bounds. Right now, you can't. Nobody can.
Visibility → Enforcement → Proof
Automated behavioral assessment. Point autoredteam at any AI system and get a map of what it actually does under stress — drift, deviation, edge cases, failure modes. Open source. Free. pip install glacis-autoredteam.
Runtime guards that sit in the inference path. Permit, deny, or escalate at the point of execution. Deterministic rules for what is known. Model-based judgment for what is ambiguous. Drift detection. Policy controls. Not after the fact — before it reaches users.
Cryptographic attestation for every decision. Notary generates tamper-evident, signed records that prove what your AI did, what policy was applied, and what the outcome was. Not logs. Evidence. Evidence that holds up when someone asks.
The Number
Every interaction that flows through Enforce and Notary feeds a single governance metric: the Glacis Score. A number from 0 to 1000. Derived from real production traffic, not self-assessments.
Think FICO for AI. Your board gets a number. Your customers get a number. Your regulator gets a number. Backed by cryptographic proof, not a vendor's word.
Proof builds itself. Every interaction attested. Every attestation improves the score. The evidence chain compounds without anyone doing extra work.
Developer-First
autoredteam surfaces the risks. Enforce stops the bad outputs. Notary proves every decision was monitored and enforced. The evidence chain closes itself.
Compliance is not the headline. Compliance is the side effect of running your AI through an enforcement layer that generates cryptographic proof. You get operational control today. The audit trail builds itself.
The Standard
The Overt standard is the open methodology for AI governance assessment. Five frameworks. 169 controls. Published at overt.is. The Glacis Score is the product that operationalizes it — turning a methodology into a measurable, verifiable number derived from production traffic.
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See what it's doing. Stop the bad stuff. Prove every interaction. Starting at $49/mo.