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Service · Knowledge + AI

Enterprise RAG and intelligent search

We turn your company knowledge base (documents, contracts, manuals, internal data) into a system that answers accurately, cites its source and respects who is allowed to see what.

Your company already has the answer. It is just buried in a thousand documents nobody can read in time.

Generative AI on its own makes things up: it answers with confidence even when it does not know. RAG (Retrieval-Augmented Generation) fixes this by grounding every answer in your real documents. But a poorly built RAG retrieves the wrong passage, ignores permissions and cites sources that do not support the answer. The difference between a RAG the leadership team trusts and one nobody uses lies in retrieval engineering: how you index, how you rank, how you cite and how you measure accuracy.

What we deliver

Ingestion and indexing

Pipelines that process PDFs, spreadsheets, wikis and databases, with chunking and enrichment designed for your domain, not generic defaults.

Semantic search with citations

Answers that point to the exact document and passage they came from, so people can trust them and check them.

Access control

The system respects who can see what: each user only retrieves what they are permitted to, even inside the same knowledge base.

Accuracy measurement

Continuous evaluation of relevance and faithfulness, so you know, in numbers, how reliable the system is before you roll it out.

What you get
  • An ingestion pipeline for your documents and data sources
  • A search and Q&A system in production, with verifiable citations
  • A permissions layer integrated with your access control
  • Relevance and faithfulness metrics for every answer
  • Source code, documented architecture and handover
Seen in production
Enterprise RAG — no vector database, with governance by department

Enterprise RAG no vector database, with governance by department

See case
Dr. JON — clinical intelligence for telemedicine

Dr. JON clinical intelligence for telemedicine

See case
Frequently asked questions
What is enterprise RAG?+

Enterprise RAG (Retrieval-Augmented Generation) is an architecture that connects an AI model to your company knowledge base. Instead of answering from the model's "general knowledge", it first retrieves the relevant passages from your documents and answers grounded in them, citing the source.

Does RAG stop AI from making up answers (hallucination)?+

It reduces it dramatically. By forcing the answer to rest on passages retrieved from your documents and showing the citation, the origin is easy to verify. We add faithfulness evaluation on top to measure and control hallucination in production.

Are my confidential documents safe?+

Yes. We design the system with per-user access control and can run it entirely on your infrastructure. Each person only retrieves what they are allowed to see.

Facing a problem like this?

Tell us the context. Within 48 hours we come back with a point of view. If it is worth doing, we move forward. If not, you leave with clarity.

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