From Prediction to
Decision.

The projects progress from domain-specific intent classification, through multimodal document understanding and agent-based orchestration, to decision support systems that translate model outputs into actionable recommendations under uncertainty.

Each POC is built end-to-end, with attention to data assumptions, model behavior, system boundaries, cost and privacy constraints, and operational trade-offs. The emphasis is not on isolated techniques, but on how ML components work together to produce reliable, practical outcomes. New projects are added as the system patterns evolve.