BMW Document Intelligence Platform

Built for BMW Group, this platform converts dense engineering specifications, validation reports, and related documentation into a structured, queryable system of knowledge. It enables teams to move from manual PDF review to an AI-assisted workflow where requirements, relationships, and inconsistencies can be surfaced across documents in minutes rather than weeks.

Engineering compliance workflows were constrained by massive document volumes, fragmented specifications, and slow manual review cycles. Validating consistency across 1,000+ page PDFs required expensive expert time and created bottlenecks for downstream engineering and decision-making.

I engineered and implemented the full-stack solution end to end: a multi-agent pipeline for document processing, Graph RAG workflows for cross-document reasoning, a graph database ontology for structured relationships, and the frontend/backend application layer used to query, validate, and inspect results. The system was designed not just to answer questions, but to produce auditable outputs teams could use in real operational workflows.

The platform replaced weeks of manual compliance review with minutes of auditable results, turning static engineering PDFs into a smart, queryable system that improves as more documents are ingested. It is deployed at BMW Group and has already removed substantial manual effort from document verification and validation workflows.