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AI/ML

Permit & Zoning RAG Assistant

Government / civic

A retrieval-augmented assistant that answers building-permit and zoning questions with citations, drawing on official municipal code, permit PDFs, and zoning tables.

The Challenge

Permit and zoning rules are scattered across dense code, PDFs, and tables — making preliminary guidance slow and hard to source reliably.

What We Built

  • An ingestion pipeline for mixed-format sources (HTML/XML code, PDFs, structured tables) into a searchable corpus.
  • Semantic search with pgvector embeddings; citation-first answers that explicitly avoid unsupported claims (no guaranteed approvals).
  • An optional OCR fallback (Azure AI Document Intelligence) for scanned inputs.

Highlights

  • Citation-first answers over official municipal sources
  • Mixed-format ingestion (code, PDFs, tables)
  • Semantic search with pgvector
  • Guardrailed scope — guidance, not guarantees