LLM & RAG Development Services
LLM and RAG development services for enterprise applications. Implement retrieval, integrations, access controls and evaluation using your accepted answer criteria.
Frequently asked questions
What is retrieval augmented generation (RAG)?
RAG combines a large language model with search over your own content, so answers are grounded in relevant, up-to-date sources.
When should we use RAG instead of fine-tuning?
RAG suits knowledge that changes or needs citations. Fine-tuning suits changing a model's style or behaviour. Many systems use RAG first.
How do you improve RAG accuracy?
By improving document preparation, chunking, retrieval and ranking, prompt design and evaluation against real questions.
Can LLMs be integrated with our existing applications?
Yes. LLM integration can add search, summarisation, drafting or assistants to existing products and internal tools through APIs.
How do you protect sensitive data in an LLM application?
With access controls on retrieved content, data minimisation, approved hosting options, logging policies and guardrails on inputs and outputs.