RAG and enterprise search

Employees need answers to questions that span contracts, policies, technical documentation and past work. A retrieval-augmented generation system connects a language model to selected sources so that it can use relevant company information when preparing an answer.

Make the answer traceable

We design the interface to show where supporting information came from. Employees can open a source, inspect the relevant passage and check its date or version. If the available material does not support an answer, the workflow should make that limitation clear.

Source citations help with verification, but they do not guarantee that an answer is correct. We test retrieval and generated responses separately, including questions with ambiguous wording, conflicting documents and no supporting information.

Keep knowledge and permissions current

The project includes how documents enter the index, how changes are detected and how removed material is excluded. We also define how permissions carry through from source systems and test attempts to retrieve restricted information.

Deployment can use an approved cloud environment or private infrastructure. The architecture describes where original files, extracted text, embeddings and application logs are stored and processed.

Launch with a defined set of questions

A useful pilot starts with a team, a set of sources and representative questions. We establish evaluation criteria before broadening the collection or adding more workflows.

Read our guide to planning an enterprise RAG pilot, or discuss how search could work within your existing tools through our integration service.