LATYNEX
Services

A company knowledge base your AI tools can actually use — organised, owned and kept current

Inventory the documents, decide what belongs, structure and clean it, set access and update rules, and test it with real questions before anyone relies on it.

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Direct answer

An AI assistant is only as useful as the knowledge behind it. Most companies have that knowledge in scattered places: shared drives, old wikis, chat threads, PDFs, people's heads. Implementation is the work of deciding what belongs in the knowledge base, organising and cleaning it, setting who may see what, giving every part an owner who keeps it current, and testing it with the questions your team and customers really ask.

It is the layer underneath AI Implementation for Business and Custom AI Agent Development: the assistant or agent can be excellent and still give poor answers from poor sources.

What an implementation covers

  • Inventory of where company knowledge lives today and who maintains it
  • Scope decisions: what the AI may draw on, and what it must never see
  • Structure: sections, naming, and the questions each part is meant to answer
  • Cleanup: duplicates, outdated versions, contradictions and gaps
  • Access rules aligned to who is allowed to see what
  • Ownership: a named person and a review rhythm for every part, so it does not decay
  • Where it lives: the shared-knowledge feature of your AI tool, a wiki such as Notion or Confluence, a shared drive, or a retrieval layer behind a custom agent
  • Testing with real questions, including ones it should refuse or hand to a person
  • A short handoff guide for whoever maintains it

Notion, wikis and drives

We work with where your knowledge already lives. Notion, Confluence, Google Drive or SharePoint can all be the home of a knowledge base; the choice is about who maintains it and what your AI tool can read, not about which product is fashionable. We do not resell any of them.

What we will not promise

We do not promise that an AI tool will never give a wrong answer. A knowledge base reduces guessing; it does not remove it, which is why testing and a human handoff path matter. We do not decide for you what is confidential: we help you draw the line and write it down. Sensitive material stays out unless you decide otherwise and the access rules allow it.

How it connects to the rest

Start with the AI Agent Knowledge Base Guide if you want the concepts first, and see Testing an AI Agent Before Launch for how answers are checked. Where the same knowledge feeds a customer-facing agent, AI Human Handoff covers when a person takes over.

How it works

  1. 1

    Inspect

    We look at what you actually have today — accounts, roles, tools, data, who uses what — read-only where the system allows it, before anyone proposes changing anything.

  2. 2

    Understand the current setup

    What works, what is duplicated, what is unowned, and where work leaks between tools. You get this in writing, in plain language.

  3. 3

    Implementation plan

    A scoped plan with clear boundaries: what gets configured, what stays as is, what is deliberately left out, and what needs a decision from you first. Scope and price are agreed in writing before configuration starts.

  4. 4

    Configure

    The plan is carried out inside your own accounts, through access you grant and can withdraw. Changes that touch people, money or customer data wait for your explicit approval.

  5. 5

    Handoff

    Documentation of what was set up and why, a short walkthrough for the people who will run it, and a clear line on what is yours to operate from now on.

Is this the right page?

  1. 1 Assess
  2. 2 Implement
  3. 3 Automate
  4. 4 Build

Choose this page if the AI tools are fine but their answers about your business are inconsistent because the sources are scattered or out of date.

What usually comes next

Not a package — only where it makes sense once this is done.

Who you would be working with

Company · Who you would be working with
LATYNEX Digital is a service line of Latynex Trade OÜ, a company registered in Estonia (EU). Contact: info@latynexdigital.com.
How we work · Delivery
Remote, in English, with the person who would run the project. No local office is implied in any market.
How we work · Commercial terms
One scope and one price, agreed in writing before work starts. Your accounts, code and domain stay yours; any access we use is granted by you and can be withdrawn.

There are no client case studies on this page, and none are implied. What LATYNEX has built and runs itself is on the portfolio, each system labelled by stage. Published prices are on the pricing page; anything not listed there is scoped and quoted after review.

Questions

Do we need a knowledge base before using ChatGPT, Claude or Gemini?+

Not to start. A team can use these tools without one. It becomes important when you want consistent, company-specific answers, when several people rely on the same material, or when an agent answers customers.

Can you work with Notion, Confluence or Google Drive?+

Yes. The knowledge base lives where it will be maintained and where your AI tool can read it. We do not resell any of these products.

Who keeps it up to date?+

A named person inside your company. Implementation sets the ownership and review rhythm, because a knowledge base with no owner decays quickly.

Will the AI still get things wrong?+

Sometimes, yes. Good sources and testing reduce it, and a human handoff path covers what remains. We do not promise error-free answers.

What happens to confidential material?+

You decide what may be included. We help draw the line and write it down, and keep sensitive material out unless you decide otherwise and the access rules allow it.

See AI Implementation for Business
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