Case Studies

Developed a multi-agent system to parse, analyze, and extract regulatory obligations from complex financial documents, reducing manual review time by 75%.

Integrated custom machine learning models with existing IoT sensor data to predict equipment failures before they occur, resulting in a 20% increase in uptime.

Implemented an LLM-powered triage system that accurately categorizes incoming support tickets and routes them to the appropriate human agents or resolves simple queries autonomously.