How I Built an AI Compliance System for Charter Aviation Using RAG and Pinecone

How I Built an AI Compliance System for Charter Aviation Using RAG and Pinecone Building RAG for compliance-critical domains is not the same as building RAG for a general-purpose chatbot. When the outputs affect an operator's certification status, wrong answers have real consequences. This is the full architecture walkthrough of Navlyt — the compliance operating system I built for charter aviation operators. Navlyt tracks FAA, Transport Canada, and EASA regulatory requirements for small charter aviation operators. It answers compliance questions, monitors obligation status, and generates required documentation. The challenge: regulatory documents are dense, cross-referenced, and version-controlled in ways that break standard RAG approaches. This article covers the complete technical implementation — chunking strategy, retrieval architecture, answer generation with citations, and the accuracy validation approach I use for a compliance-critical domain. The Problem With Standard RAG for R