Medical Documentation Agents
A LangGraph and LangChain agent system with LangSmith evaluation, built for complex medical and device documentation work—combining autonomous assistance with safeguards, strong retrieval, and layered knowledge.
Overview
This project packages agent workflows suited to regulated documentation: tool use with reversible changes, evaluation environments that mirror production constraints, hybrid search over large technical corpora, and explicit separation between evergreen reference material and client-specific facts. Documentation in the repository describes the architecture, setup, and evaluation layers in depth.
Highlights
Controlled autonomy
Mutating operations capture state before execution and support rollback workflows, with audit metadata for traceability.
Realistic evaluation
Dual endpoints and seeded mock data let teams stress-test agents without risking production writes.
Hybrid retrieval
Dense vector search combined with sparse retrieval, metadata filters, and optional re-ranking for device and regulatory content.
Knowledge architecture
Distinct global and client knowledge scopes with conflict detection and unified query behaviour.
Long-running tasks
Segmented buffers, hierarchical planning, compression, checkpoints, and a final review pass to limit drift on multi-document work.
Quality measurement
LangSmith integration supports systematic evaluation of agent outputs alongside the documented test strategy.
Visual summary
Technology stack
- LangGraph
- LangChain
- LangSmith
- Python
- Qdrant
- BM25 / hybrid search
Extended architecture notes live in the repository Documentation folder (quick start, setup, code documentation, evaluation layer, knowledge layer, and flow diagrams).
Exploring Agentic documentation for medtech or life sciences?
Get in touch