model-governance

A governed local AI build-and-memory system that trains small brains, compares them, protects the better one, archives the worse one, and preserves the evidence of why. v1.0.0/governed-v2.2.0+

A beginner-friendly AI Governance & Risk Toolkit — risk register, governance templates, and audit-ready workflows for early-stage AI teams.

Forkit Core is an open source passport layer for AI models and agents with GitHub CI validation, local verification, and Hugging Face-compatible export.

Open-source model inventory & governance. Discovers every model, rule, and pipeline across all your platforms as one immutable, agent-queryable graph — git for models.

A practical framework for turning data analysis into decision policies you can defend. Covers risk modeling, thresholding, exception handling, policy cards, monitoring, and update triggers, using real patterns like abstention rules, reorder points, and fairness-aware benchmarking. Built for “ship it” data science.

Automated validation toolkit for tabular ML models in finance and regulated domains.

Five Tests Standard (5TS): a vendor-neutral published standard for verifiable AI governance through proof-carrying decisions. Includes schemas, machine-checkable conformance vectors, and a reference validator.

Audit-ready explainability artifacts (reason codes, model cards, drift checks) for scikit-learn investment & credit-risk models.

Compliance-as-code for AI systems: evaluate AI apps against EU AI Act, NIST AI RMF, and OPA/Rego policies.

Depth-tracked regulatory audit primitives for privacy-preserving AI audits with signed envelopes and TenSEAL CKKS support.

Data Trust Engineering (DTE) is a vendor-neutral, engineering-first approach to building trusted, Data, Analytics and AI-ready data systems. This repo hosts the Manifesto, Patterns, and the Trust Dashboard MVP.

Protected v1.0.0 baseline for ARC-Neuron LLMBuilder — local-first LLM lifecycle tooling for benchmark receipts, candidate promotion, lineage, and governed model improvement.

EU AI Act governance prototype that turns real medical AI evidence and ISO/IEC 42001 governance scaffolding into reviewable classification, evidence checks, human oversight, and incident-handling paths.

Institutional Stock Risk Engine & Governance Framework

This project allows data science teams to orchestrate their model governance processes. Ensuring models built for production environments are gated properly with the adequate flags pointing to data and/or model artefacts to review.

Compile tree-ensemble models into deterministic, auditable decision artifacts — score, calibrated PD, risk bands, and adverse-action reason codes in one hashed JSON that produces identical integers in Python, SQL, and COBOL.

Self-hosted enterprise agent platform for model governance, RAG, tools, approvals, conversations, audit logs, and runtime observability.

Taurus: risk-first autonomous trading platform with auditable decisions, broker reconciliation, model governance, and demo/live readiness controls.

Secure ML release control plane with deterministic policy gates, artifact signing, Kubernetes deployment, observability, rollback, and advisory AI release intelligence.

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