Routing Medical Claims with an Intelligent Agent: Deterministic Logic Meets Structured AI Output

Routing Medical Claims with an Intelligent Agent: Deterministic Logic Meets Structured AI Output How I Built a Claims Prioritization Engine Using Agent Workflows, Tool Calls, and Pydantic-Validated Outputs TL;DR Hospital billing departments receive hundreds — sometimes thousands — of insurance claims per day. Every one of them needs to be triaged, sorted, and assigned to the right specialist before money can flow. In this experimental project, I built an agentic pipeline called ClaimsRouter-AI that handles this automatically. The agent runs a chain of deterministic, rule-based tools first (no LLM involved at the computation stage), then hands the results to a Gemini model for structured reasoning, and finally validates every output through a Pydantic v2 schema. The result is a system that routes a batch of 50 synthetic claims in under a second, assigns each to the correct revenue cycle queue, and produces a complete audit trail of every decision — including which tool computed what, an