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.

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

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

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.

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.

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

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

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

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