Real systems. Real clients. Real numbers.

The client's maintenance teams were responding to equipment failures after they happened. We built a predictive maintenance system using sensor data and computer vision that flags failure risk 72 hours before it becomes an incident.

A subscription business can see customers churning after the fact, with no way to act before they leave. We'd build a churn-prediction model that flags at-risk accounts weeks in advance.

Manual dispatch coordination across 400 routes was creating costly errors. We built and deployed a multi-agent system that handles scheduling, exception management, and escalation.

In past roles, our team built GenAI systems that drafted credit memos from structured data, automating documentation while keeping compliance review in the loop.