Scaling AI Agent Architecture for Enterprise Supply Chain Operations

A global agricultural machinery and heavy equipment manufacturer engaged deepsense.ai to assess and scale AI agent prototypes for supply chain operations. The six-week advisory engagement covered architecture review, target-state design, evaluation, observability, context management, integration guidance, proofs of concept, and workshops. During implementation and optimization, time to first token improved 2–3x, end-to-end response time improved 20%, tool calls per question fell 75%, and output tokens fell 50%. The platform later moved into production use.