Accountable Autonomy: open-source evidence layer that gates every AI agent tool call against your policy and writes a hash-chained record an auditor verifies offline, without trusting you. Root-agnostic; binds to TPM 2.0 / SEV-SNP when present. Your environment, no SaaS, no telemetry. AGPL-3.0.

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.

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

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

Real-time EU AI Act Article 12 compliance dashboard for AI agent decisions. Log decisions as they happen, track oversight gaps, export evidence packages.

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

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.

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

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.