Enterprise RAG & Knowledge Systems
Every organisation has the answer written down somewhere and no way to find it. Retrieval-augmented generation fixes that properly only when the retrieval is good — which is a data engineering problem long before it is a model problem. We build knowledge systems that ingest your documents, respect who is allowed to see what, cite their sources so answers can be checked, and say "not in the material" rather than inventing something plausible.
How we work on this
- Corpus assessment — what you have, what state it is in, what is retrievable
- Retrieval prototype — measured on a real question set from your teams
- Production system — permissions, sync, citations, evaluation
- Knowledge operations — gap reporting and continuous improvement
Our Capabilities
Comprehensive Enterprise RAG capabilities backed by deep expertise and proven methodologies.
Technologies We Use
We leverage industry-leading tools and frameworks to build robust, scalable solutions.
What we would tell you in the first meeting
When a retrieval system gives a bad answer, the model is usually not at fault — it answered faithfully from the wrong passages. Fix retrieval quality first. It is unglamorous work and it is where essentially all of the improvement lives.
Enterprise RAG — Frequently Asked Questions
Why do retrieval projects underperform?+
Almost always because retrieval quality is poor, not because the model is weak. If the wrong passages reach the model, it answers faithfully from the wrong material. Chunking that ignores document structure, pure vector search where exact identifiers matter, and no reranking are the three usual causes — and all three are data engineering problems rather than model problems.
How do you handle permissions, so people only see what they should?+
Retrieval is filtered by the access rules you already enforce elsewhere, applied at query time rather than bolted on afterwards. If a user cannot open a document in the source system, no passage from it can reach their answer. Getting this wrong is the fastest way to turn a knowledge system into a data breach.
What happens when the answer is not in our documents?+
It says so. Refusal is designed behaviour, not a failure — a system that invents a plausible answer to an unanswerable question is worse than one that returns nothing. We also report those questions back to you, because a list of what your documentation does not cover is genuinely useful.
Related Services
Ready to Get Started with Enterprise RAG?
Tell us what you are trying to build and what is in your way. We will tell you how we would approach it — including when the answer is that you do not need us.
Talk to an engineer