Part of
AI implementation for business

The knowledge exists. Finding it is the problem

In most companies we have looked at, the answer to an employee's question existed in a document from two years ago.

Keyword search didn't find it, because the document called the same thing something else.

Who it's for
3

Who this is for

  • Organisations with knowledge scattered across drives and systems
  • Teams where onboarding means asking colleagues
  • Companies running projects where the same thing has been solved before
Scope
4

What it covers

Indexing what you already have

Documents, procedures, proposals, notes and tickets from the systems you already use.

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Without moving everything into a new tool — migrating knowledge into yet another place is the most common reason such projects die.

Search by meaning

A question in your own words finds a document that uses different terminology.

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That is the difference between "there isn't one" and "there is, it's just called something else".

Permissions respected in results

Search must not show somebody a document they have no access to.

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It sounds obvious and is the most commonly skipped requirement in this kind of rollout.

Answers with their source

A summary with a link to the document it came from.

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The employee has to be able to check — otherwise the tool is only a faster way to get an uncertain answer.

In depth
In depth

How to check this before a project

Collect ten questions somebody asked in the company chat last month instead of looking the answer up. If the answers exist in documents, the project makes sense and can be measured.

What we don't promise

We don't promise the tool will tidy up disorganised documentation. Semantic search softens the effects of dispersion, but contradictory procedures stay contradictory — it just becomes easier to notice.

Questions
3

Questions about this scope

Will our documents go to an external model?

That is the first thing we settle, and there are several options: a model running in your infrastructure, a provider contractually barred from training on your data, or an architecture where the model only ever sees the fragment needed to answer. The choice depends on how sensitive the content is.

How many documents does this need?

Volume isn't the deciding factor — dispersion is, along with how often somebody is looking for something. With five hundred documents in one well-named folder, ordinary search is enough, and we will say so.

Does it update itself as documents are added?

Yes, the index refreshes automatically. It is worth knowing that it will also surface out-of-date documents — which is why these rollouts usually expose a need to mark what still applies.

Got an idea? Let's talk.

The first call is free. We reply within one business day.