AI Systems Lab

Live environments where decision logic and interface behavior are tested under real constraints.

Each system targets a specific failure mode — latency, opacity, fragility — and ships with measured outcomes.

Applied MLFeatured

AI Business Location Predictor

Predicts optimal business locations by scoring 30+ variables against revenue outcomes.

XGBoostGeoPandasPostGISCensus APIFoliumFastAPI

Problem

Multi-agent systems produce opaque decision chains that are hard to debug under load.

System

Maps model decisions, tool calls, and latency patterns into a single cinematic operator view with trace replay.

Impact

Reduced mean debug time from 45min to 8min in agent orchestration workflows.

Problem

Most animation systems prioritize spectacle over accessibility and user intent.

System

Cinematic motion framework where scroll, hover, and focus transitions add signal — respecting reduced-motion preferences by default.

Impact

Zero accessibility regressions across 12 interface iterations.

Problem

Production AI systems fail on edge cases that unit tests and manual QA miss entirely.

System

Evaluation rig that generates adversarial inputs, tracks regression across model versions, and produces scored output comparisons.

Impact

Caught 3 critical regressions before production deployment across 2 AI product lines.