Enterprise RAG Chatbot & Intelligent Agent Development

Generic AI models lack access to your internal databases, PDFs, compliance handbooks, and customer histories. Fine-tuning models directly is expensive and quickly becomes obsolete as your data evolves daily. Production RAG (Retrieval-Augmented Generation) solves this by fetching your live, authorized company data at query time and injecting it directly into the LLM's prompt context.

We engineer the full data ingestion lifecycle: smart document parsing (PDFs, Markdown, audio transcripts, SQL records), recursive chunking with semantic overlap, hybrid vector + keyword search (BM25), and re-ranking models (Cohere Rerank) to guarantee that only the most relevant passages enter the reasoning window.

Security is engineered into the foundation. We enforce strict organizational role-based access control (RBAC) directly inside PostgreSQL via pgvector, ensuring executive-level documents are never accessible to unauthorized users.