AI Knowledge Systems

Company knowledge your team can trust and use.

We connect your documents, systems and expert knowledge so people can find supported answers and complete useful work. We start with a focused use case, improve the sources it depends on, and keep subject-matter experts involved after launch.

Discuss your project

Four principles

01Trusted sources
02Expert ownership
03Useful workflows
04Continuous evaluation

Knowledge that stays useful

Four recurring activities, not a one-off project. Real use improves the sources, the answers and the workflows around them.

Expert ownershipTrust · Exceptions
Review
Activity 01

Curate sources

Identify the documents, systems and expert knowledge the chosen use case depends on, and who owns each one.

Where experts own it

Experts approve the sources. Approved sources remain the reference; derived content stays linked to them.

Expected evidence

Source map with named owners and review status.

Your experts stay essential

Your experts identify reliable sources, explain exceptions, validate difficult answers and keep knowledge current.

AI reduces repetitive retrieval and drafting so they can focus on decisions that need experience.

What retrieval actually does

Retrieval-augmented generation (RAG) brings relevant source material into an AI response. It is one part of a knowledge system, alongside search, permissions, connected tools and evaluation.

Approved sources remain the reference; derived content stays linked to them. Each source carries evidence and a review status rather than an unexplained confidence score — a retrieval similarity score is not the probability that an answer is correct.

The architecture underneath

Layers, not stages
  1. L1Sources and ownershipApproved documents and systems, each with a named owner and review status.
  2. L2Structure and metadataTaxonomy, document structure and the metadata that makes material findable.
  3. L3Retrieval and permissionsSearch and retrieval that respect the access rules already in place.
  4. L4Context and toolsContext engineering: instructions, retrieved material, tool outputs and task state, with connected systems inside agreed limits.
  5. L5Interfaces and evaluationWhere people meet the system, and the evaluations and traces that show how it behaves.

Access and actions

Existing access rules apply to retrieval and tool use. Actions have agreed limits, with approval where their consequences require it.

Sensitive reads still need authorisation. Not every read should require a manual approval, or the system stops being useful.

How we measure it

  • Time to find an answer
  • Supported-answer quality
  • Successful task completion
  • Expert review effort
  • Cost and response time

We establish a baseline first and compare against it. We publish efficiency claims only from real measurements.

Where an engagement starts

An assessment around one use case.

Scope and duration are agreed around the use case you choose, before the work begins.

Discuss your project
  • A map of sources and owners
  • A record of gaps and risks
  • A proposed architecture
  • A prioritised plan
  • A starter evaluation set