Custom RAG Pipeline

What is a Custom RAG Pipeline?

While PrivateGPT provides an excellent out-of-the-box document Q&A experience, a Custom RAG Pipeline is a bespoke, production-grade system designed for your specific data types, query patterns, and accuracy requirements. It goes beyond plug-and-play to deliver enterprise-level precision.

We design the pipeline around your actual data: choosing the optimal chunking strategy (semantic, recursive, or fixed-size), selecting the best embedding model for your domain (legal, medical, technical, multilingual), configuring the vector store with appropriate indexing parameters, and implementing query routing and re-ranking to maximise answer quality.

The result is an AI system that doesn't just search your documents — it understands them. It can handle complex multi-hop questions that require cross-referencing multiple sources, provide cited answers with page numbers and document names, and maintain context across long conversations about your data.

This service includes a thorough requirements consultation, pipeline architecture design, implementation, testing with your actual data, and a handover session. We also provide documentation for your team to maintain and extend the system independently.

How It Works

A production-grade pipeline from data ingestion to cited answers.

What You Get

• Requirements consultation — deep-dive into your data types, query patterns, and accuracy needs
• Custom chunking strategy — optimised for your document formats and content structure
• Domain-specific embeddings — embedding model selected and fine-tuned for your industry
• Vector store with indexing — configured for fast, accurate retrieval at scale
• Query routing & re-ranking — multi-stage retrieval for maximum answer quality
• Cited answers — responses include source document names, page numbers, and relevant passages
• Documentation & handover — complete system docs and 1-hour training session for your team

Who Is This For?