Capability
Document Intelligence
RAG pipelines that connect AI to real data. Ask a question across thousands of documents, get a sourced answer in seconds.
Overview
Retrieval-Augmented Generation (RAG) connects AI to actual data: contracts, policies, knowledge bases, technical documentation. Instead of hallucinating answers, the system retrieves the relevant passages, generates a grounded response, and cites every source. Automated ingestion keeps the index in sync as data evolves, so the answers are always current.
How It Works
Intelligent Chunking
Documents are split using context-aware strategies adapted to each content type. Narratives use semantic boundaries, tables and forms use structured extraction. Chunk sizes are tuned per corpus for optimal retrieval.
Hybrid Search
Vector embeddings capture meaning while keyword search catches exact terms. Combined with metadata filtering and reranking, the system surfaces the most relevant passages even in large collections.
Multiple Formats
Text, PDFs, structured documents, and various file types are all processed and indexed for search.
Citations & Verification
Every answer includes source references with document names and relevance scores. Claims can be traced back to the original passage.