Knowledge base search
Replace keyword search over a wiki or shared drive with answers that quote the relevant policy and link to the full page.
Capability
Answers grounded in your own knowledge.
We build search and assistant products on top of your documents and records, with retrieval, citations and evaluation, so answers can be checked instead of trusted blindly.
Overview
Language models, pointed at your material.
A general model knows a great deal about the world and nothing about your business. Retrieval augmented generation closes that gap: your documents, policies, tickets and records are indexed, searched and passed to the model as evidence, so the answer reflects what your organization actually knows. The model stays general; the evidence makes it specific.
That is only the start. We build the ingestion pipeline, the search layer and the prompt that holds it together, then test the whole thing against real questions from your team. Citations, access control and clear fallbacks are part of the design, not an afterthought. Because the sources are known, a wrong answer can be traced back to a missing document or a weak search result.
Retrieval that finds the right passage
Chunking, embeddings and vector search tuned to your material, with keyword search blended in for names, codes and exact phrases.
Answers with citations
Every answer points back to the source passage it used, so a reader can verify it in seconds rather than taking it on faith.
Evaluation from real questions
We build a test set from questions your team actually asks and measure relevance, grounding and refusal before launch.
Access control respected
Retrieval honors the permissions of the person asking, so a document they cannot open never appears in their answer.
Ingestion that keeps up
Scheduled and incremental indexing for documents that change, with parsing for PDFs, spreadsheets, web pages and internal wikis.
Model choice kept open
We keep the model layer replaceable, so a better or cheaper option can be adopted without rebuilding the whole system.
Use cases
Where grounded answers help
The strongest first projects have a large body of written knowledge and a team that spends time searching it.
Support answer drafting
Give agents a draft reply grounded in product documentation, past tickets and the customer's own history, ready to edit.
Policy and contract review
Ask questions across long documents and get answers with the exact clause attached, so reviewers can check the source.
Onboarding copilot
New hires ask questions in plain language and get answers from internal documentation instead of interrupting a colleague.
How we work
How a grounded system gets built.
Discover
We inventory your sources with your team, check their quality and permissions, and collect the questions they need answered.
Design
We choose the chunking, search and prompt strategy, then test the approach on a sample before committing to a build.
Build
We build ingestion, retrieval and the interface together, with an evaluation suite that runs on every change so regressions show up early.
Support
We monitor answer quality and source coverage, refresh the index as documents change and tune retrieval as usage grows.
FAQ
Common questions.
Do we need to move our documents?
No. We can index documents where they already live, or copy them into a store you control. Either way, access rules follow the source system.
What happens when the answer is not in the documents?
The system says so and offers the closest sources. A clear refusal is better than a confident guess, and we test for it.
How do you measure quality?
We use a test set of real questions with known good answers, then check relevance, grounding and refusals before and after each change.
Can this run inside our cloud?
Yes. Retrieval, storage and model access can all run in your AWS or Azure environment, using models you approve.
Next step
Start the conversation
Have a body of knowledge worth searching?
Send us a sample of the documents and the questions your team asks. We will tell you what retrieval can realistically do with them.