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RAG system development

Give your team useful answers from the knowledge you already own

Make documents, policies and business knowledge easier to search with an AI assistant built around your users and your data.

For businesses and political organisations with information spread across documents, websites and internal systems.

Discuss this project

What I can deliver

  • Document ingestion and a reliable update process
  • Vector, lexical or graph retrieval selected for your questions
  • Answers with source references and permission checks
  • A user interface and an admin dashboard for managing the system
  • Evaluation, deployment and operational monitoring

How I approach the work

I start with your documents and representative questions. We test a small retrieval baseline, review the evidence behind the answers and add graph retrieval or temporal memory when the use case calls for it.

Relevant experience

I have built RAG systems for B2B businesses and political organisations, including the retrieval pipelines, chat interfaces and admin dashboards around them.

How I choose a RAG architecture

Choosing the technology

PostgreSQL, Supabase pgvector, Neo4j, LightRAG, Graphiti and model integrations. The final stack depends on your data, access requirements and hosting preferences.

Questions about this service

What is a RAG system?

Retrieval augmented generation, or RAG, retrieves relevant information from your approved sources before an AI model answers. A business implementation also needs source references, access controls, a process for updating documents and a way to evaluate answer quality.

Do I need a vector database or a knowledge graph?

That depends on the questions your users ask. I compare lexical and vector retrieval first, then evaluate a graph when relationships or changing historical context are central to the product.

Can the assistant use private business documents?

Yes. We define the permitted data sources, user access rules and hosting requirements before implementation. Retrieval and document access need to follow the same permission boundaries as the application.