Document Intelligence & RAG Systems

Turn unstructured documents into actionable intelligence

Document intelligence systems that transform how you work with PDFs, contracts, invoices, and other documents. I build production-ready pipelines that extract structured data, enable semantic search, and answer questions across large document collections. These systems combine OCR, intelligent extraction, and RAG (Retrieval Augmented Generation) to make your documents searchable, queryable, and actionable. Whether processing legal contracts, financial documents, or technical manuals, I engineer systems that maintain accuracy while handling scale.

What I Build

  • OCR and document parsing pipelines for PDFs, DOCX, and images
  • Structured data extraction with validation and error handling
  • Vector search systems with hybrid keyword + semantic search
  • RAG pipelines with accurate citation and source attribution
  • Document Q&A systems that answer questions across collections
  • Multi-tenant document management with workspace isolation
  • Background processing queues for large document batches
  • Document comparison and change detection systems
  • Automated document classification and routing
  • Evidence pack generation with highlighted excerpts

Technologies

I use a comprehensive stack of production-ready technologies to build reliable systems:

Model Provider APIsEmbedding ModelsLangChainLangGraphInstructorPyMuPDFpython-docxTesseract OCRPaddleOCRVector DatabasesChromaDBPineconeQdrantWeaviateFastAPIPostgreSQLRedisCeleryDockerTypeScriptPythonAWS S3Cloud Functions

Capabilities

OCR & parsing
Structured extraction
Vector search
Retrieval evals
Multi-format support
Batch processing
Citation accuracy
Cost optimization
Real-time indexing
Document versioning