Knowledge assistants & RAG
Your business knowledge. Ready when it is needed.
Start with one team, a manageable collection of approved documents and the questions people repeatedly ask. We scope an assistant that retrieves relevant material, points back to its sources and makes missing information visible.
What we can
put in place.
- A source inventory with owners, access rules and update requirements
- A retrieval design suited to the documents and questions
- Answers with supporting source references where available
- An explicit fallback for missing or conflicting information
- Evaluation examples for retrieval relevance and answer grounding
- A source-update process and handover for the people maintaining it
From idea to everyday use
A clear route
to the first version.
- 01
Choose the team, document owners and recurring questions for the first scope
- 02
Agree source versions, access rules and what the assistant must not answer
- 03
Test ordinary questions alongside missing, conflicting and restricted information
- 04
Review the results, document the limitations and agree how source changes will be maintained
Agree the boundaries.
Measure what matters.
Retrieval-augmented generation (RAG) gives a model relevant source material when answering; it does not guarantee correctness. Private documents require identity and access controls applied before retrieval. Data providers, retention and permitted document types are agreed for each project.
How a first project usually works
One job.
A checkable path.
The same sequence on every scoped AI project, before anything depends on the system.
- 01
Free 30-minute conversation about one specific job.
- 02
Written scope that separates the build, ongoing care, and AI usage.
- 03
Test the full path, including failure cases.
- 04
Human review before anything goes out.
- 05
Logs, limits, and a way to stop it.
Before we begin
Your questions,
answered.
What could a first project look like?
For example, a team might start with an approved onboarding handbook and a set of recurring process questions. A useful answer would identify the relevant passage and its source. If the handbook does not cover the question, the assistant should explain the gap and direct it to the agreed owner. This is an illustrative scope, not a case study or a promise that your documents are ready.
What should we bring to an initial discussion?
Bring a description of the team, the questions it needs answered and who owns the documents. Start with a non-sensitive sample or an inventory; agree the handling and access arrangements before sharing private material. Current versions, known contradictions and update frequency are useful inputs.
Is this the same as training a new model?
No. Retrieval-augmented generation supplies relevant source material when a question is answered. Fine-tuning is a separate decision and is not assumed in this service. Retrieval can help grounding, but it does not guarantee a correct answer.
Can different staff see different information?
That requires authenticated users and permissions enforced before private information is retrieved. We scope and test the relevant boundaries. A hidden link or an instruction telling the model to keep a secret is not a substitute for access control.
How do we decide whether the first version is useful?
Agree test questions and acceptable responses before evaluating it. Include questions with a clear source, questions without an answer, conflicting documents and restricted information. Review the actual answers and references; a convincing demonstration on a few easy questions is not sufficient evidence for broader rollout.
Who keeps the information current?
The source-update process and responsibilities are part of the agreed project scope. Identify an owner for each source and a way to handle withdrawn or superseded documents. An assistant cannot make an outdated policy authoritative.
Your next AI project starts here
Bring the challenge.
Let’s build the AI.
Show us the task, the information and the tools involved. We’ll help you shape a useful first project.