Project Panacea: AI Healthcare Facility Quality Recommender
AI Healthcare Facility Quality Recommender
¶ 01Context & Design Rationale
“A reliable system is designed not around hypothetical optimal conditions, but around deterministic resilience under resource pressure.”
AI-powered healthcare facility recommendation system with full traceability. A Next.js frontend posts search queries to a FastAPI backend that runs a multi-step pipeline: facility search, data extraction, cross-verification across sources, trust scoring, and ranking. Results are surfaced with verifiable trust scores, distance metrics, and insurance compatibility, helping patients make informed care decisions. Engineered with strict architectural boundaries, deterministic memory models, and zero extraneous runtime dependencies.
¶ 02Architectural Pipeline
SUBSYSTEM RUNTIMEINGESTION PHASE
Protocol Parser
Zero-Copy Frame
→
TRANSFORMATION
Core Logic Unit
Deterministic Arena
→
PERSISTENCE
Storage / State Layer
Atomic Append