AI system registry and governance tracker with EU AI Act risk classification, impact assessments, and a compliance dashboard — built for legal and compliance teams.

A machine learning tool that predicts the risk of loan default using borrower financial data and outputs model probabilities and classifications from logistic regression, XGBoost, and a neural network.

Claude Code plugin for structured change management — risk classification (P0-P3), multi-domain collaborative analysis, adversarial spec review, implementation verification, and business impact analysis.

Governance control plane for EU AI Act compliance — system registry, risk classification, evidence RAG, eval gates, data-contract drift monitoring, and audit-ready evidence packs

Experimental Claude Code skill for solo builders: structured prompts and reference checklists that surface the invisible production layer (security, GDPR, scaling, bus factor) of any build. No warranty; not legal or security advice.

Enterprise IAM governance pipeline — maps 75 applications to IAM products, classifies risk, detects governance gaps, and produces management dashboards with remediation queues and department scorecards.

Injury prediction model using machine learning to analyze factors like workload, player metrics, and environmental conditions. It identifies injury risk patterns early, enabling preventive actions, improved training decisions, and reduced injury occurrence in athletes.

LLM complaint insights: Structured summaries, risk tags, and entity extraction on CFPB consumer complaints — built with OpenAI + LangChain, MLflow, Streamlit.

Guardrail API for detecting personalized mental-health advice with explainable safe/unsafe decisions. Docker-first, FastAPI, Cloud Run-ready, with auth, rate limits, and cost controls.

This project uses a public vehicle trajectory dataset (proxy) to simulate real-time driving signals.

A FastAPI service that classifies AI use cases against EU AI Act risk tiers: Unacceptable, High, Limited, or Minimal risk.

Reference repository outlining protocol-level risk and liability classification concepts; taxonomy reference, not insurance or financial advice.

120-Tool Autonomous AI Command Center - EU AI Act Compliance - Multi-Agent MCP + A2A Protocol - Nexus Control Center

Machine learning-based mental health risk prediction system using XGBoost, Flask REST APIs, Docker, and behavioral analytics for early depression risk assessment.

Research on systemic failures in AI applications identified through news media, exploring risk factors and mitigation taxonomies.

Deterministic EU AI Act classifier with cited risk tiers, obligations, timelines, CLI, MCP-style tools and review gates.

Automated EU AI Act (2024/1689) compliance checker: classify risk, check obligations, generate audit-ready reports and dashboards.