AI Knowledge Bases

Put company knowledge to work.

Connect your documents, procedures and product information to an AI knowledge base that helps your team find, check and use answers as the business grows.

Built around your information, your tools and the people who use them.

An answer you can checkIllustrative example

“What do we need before a client project can start?”

Before the kickoff, confirm:

  1. The scope is approved.
  2. A project owner is assigned.
  3. The required account access is in place.
View example source
Client onboarding guide · Getting started

“Schedule the kickoff once the scope has been approved, the project owner has been assigned and the required account access is in place.”

Fictional source material created for this example.

Your team’s answers would link back to the approved material they came from.

More people should mean
more capacity.

As the business grows, more questions land with the people who have been there longest. New starters need guidance. Sales needs product details. Delivery needs to know what was agreed.

A useful knowledge base makes that information available across the team. People can find the current guidance, check the source and move the work forward without making one person the default answer to everything.

The result to build toward: more people able to do good work independently.

Where the knowledge becomes useful.

Start with the questions that affect delivery, customer conversations or getting new people up to speed. Each use needs the right sources and a clear audience.

Operations and onboarding

Give new starters and existing team members a way to look up procedures, responsibilities and approved ways of working. Experienced colleagues can spend more of their attention on exceptions and decisions.

Example question“What needs to happen before we start a new client project?”

Sales and product knowledge

Bring product details, service scope and approved commercial guidance into reach during a customer conversation. Help the team check what is available and avoid promises the business cannot deliver.

Example question“Does this service include setup, and what falls outside the scope?”

Customer support

Give support staff a shared reference for product questions and troubleshooting. A customer-facing version can use a separately approved collection, with a defined route to human support.

Example question“Which checks should I try before this issue needs a specialist?”

Delivery and technical work

Help people find the relevant instructions, project documentation and lessons that have been recorded. Make useful experience available beyond the person or project that first produced it.

Example question“Which procedure applies to this installation, and where is the current guide?”

From a question to a usable answer.

The system finds relevant information from the sources you choose, then uses it to prepare a response. This approach is commonly called retrieval-augmented generation, or RAG.

  1. Ask a question

    People use their own words to describe what they need.

  2. Find the material

    The system retrieves relevant passages within the user’s access.

  3. Read the answer

    The response brings the useful information together with source references.

  4. Check and act

    Open the source for context, follow the guidance or ask a person for help.

When the available material does not support an answer, we configure a clear fallback: ask for more context, show the relevant documents or refer the question to a person.

A knowledge base your business can keep using.

We scope the content, connections and answer experience together. The work includes how the system will be maintained after launch.

A defined source collection

We identify the material worth including, its owner and the authoritative version. Conflicting guidance and gaps go back to the right person for resolution.

Prepared, searchable content

We organise the agreed documents so relevant passages can be found. Source titles, links and useful context stay connected to the content.

An answer experience that fits

We build a search or question-and-answer interface for the chosen team. Where appropriate, we connect it to an existing workspace after checking its integration options.

Access and answer boundaries

We implement the agreed access rules, source references and fallback behaviour. Restricted material is tested with different user roles before rollout.

Content updates and ownership

We define how revised or removed documents reach the system, how failures are flagged and who keeps the guidance current.

Testing and handover

Your team reviews representative questions, difficult cases and missing answers. We document how to use, maintain and improve the finished system.

Start with the information you already maintain.

Documents, standard operating procedures, product guides, help articles and approved answers. We check the formats, permissions and available connections before agreeing what to include.

Start with one team.
Test real questions.

Choose an area where questions recur and the source material has a clear owner. We build a focused first version, review it with the people who will use it and expand when the results support it.

See how we work

What we check before a wider rollout

  • Useful answers. Can people complete the task from the answer and its references?
  • The right boundaries. Does each user receive only the content they are allowed to access?
  • Missing information. What happens when the answer is absent, ambiguous or out of date?
  • Everyday running. Do updates, response times and usage costs fit the way your team works?

The team’s feedback becomes a practical list of improvements to the answers, the source content and the workflow.

Before you connect your knowledge.

Does our documentation need to be perfect?

No. A focused collection is a sensible starting point. We help identify the important sources, outdated versions and gaps. Your team still needs to confirm what is correct and provide knowledge that has not yet been documented.

Are you training an AI model on our files?

Usually, the system retrieves relevant material when a question is asked and supplies it to the model as context. That is different from training a new model. We review the selected providers’ data handling, retention and settings as part of the scope.

Can different teams have different access?

Yes, when the chosen tools and identity setup support the required controls. We check that during discovery, implement the agreed rules and test restricted questions. Access controls must apply to retrieved content as well as the original files.

What happens when it cannot find an answer?

We set rules for asking a clarifying question, showing useful source material or referring the request to a person. AI can still return an incorrect answer, so we test the references and fallback behaviour against realistic questions.

How does the information stay current?

We agree an update method that fits the sources: a scheduled sync, an event-driven connection or a managed publishing step. The plan also covers deletions, changed permissions and failed updates. Each content area needs an owner.

Can it take actions as well as answer questions?

That can be scoped separately through Workflow Automation or Customer Service. Looking up guidance and changing a business record need different permissions and checks. We define approvals and handoffs before giving the system actions to perform.

How long does a project take, and what does it cost?

That depends on the source quality, number of systems, access requirements and where people will use it. We agree a focused first scope and explain the build cost, expected running costs and maintenance responsibilities before work begins.

A practical starting point

Show us where the answers get stuck.

Bring a few recurring questions and examples of the documents people search today. We will help you choose a useful first scope and identify what needs to be connected, clarified or written down.

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