Model Risk · Responsible AI · MLOps · Release Safety
Problem fit: ML serving, monitoring, data quality, drift detection, governed releases and production-readiness reviews.
System
A deterministic governance system testing whether unsafe data and model changes are blocked through independent quality, drift, fairness, integrity, promotion, rollback and incident controls.
Strongest proofTagged v1.0.1 release with independent fail-closed controls
Problem fit: quantitative research platforms combining analytical computation, document retrieval and source-grounded AI explanations.
System
A research system that evaluates constrained portfolio strategies and produces source-grounded explanations without allowing generated text to change allocations.
Strongest proofEqual weighting outperformed the optimized strategy on return and Sharpe in the documented walk-forward evaluation