A single-file Python CLI that pre-registers AI/ML accuracy claims with SHA-256. Lock the threshold before the data, or it didn't happen.

Open-source evidence layer for AI governance. Gates every AI agent tool call against your policy and writes a hash-chained execution record an auditor verifies offline, now bound to TPM 2.0 + IMA hardware attestation so a regulator can check it without trusting the operator. Your environment, no SaaS, no telemetry. Apache 2.0.

Audit chain + codification gate SDK for Go agents. EU AI Act Article 12 compliance tooling.

Tamper-evident audit logs for production AI systems. Hash-chained, signed, customer-owned. TypeScript + Python SDKs designed to support EU AI Act Article 12.

Open verification infrastructure for EU AI Act Article 12 evidence — Rust library for tamper-evident audit logs

MLflow plugin: automatic PRML manifest hash tagging for runs. Pre-Registered ML Manifest evidence layer.

PRML pre-registration adapter for Inspect AI eval logs. MIT.

Field manual for the PRML v0.1 specification. 13 patterns, 4 anti-patterns, 4 working examples. CC0.

Verify PRML (Pre-Registered ML Manifest) commitments in CI. Block merges on tampered or regressed eval claims.

JavaScript reference implementation of the PRML (Pre-Registered ML Manifest) v0.1 specification. Byte-equivalent to the Python reference across 20 conformance vectors. Zero runtime dependencies.

Public scorecard of how 25+ ML eval claims meet 9 PRML falsifiability criteria. CC0 data; MIT tooling.