Custom AI Solutions

Custom AI solutions are assistants that know an organisation's own documents and data, ground their answers in those sources and cite them. We design and build them using a RAG (Retrieval-Augmented Generation) architecture.

Who is it for?

  • Organisations with many internal documents, policies or technical knowledge bases
  • Teams that want to answer frequent employee or customer questions quickly and consistently
  • Those frustrated that general-purpose chatbots do not know company-specific information

How we work

The steps show a general framework; scope and duration are adapted to each organisation.

  1. Identifying data sources

    We decide which of your PDFs, emails, databases and document systems will be used, and under whose access rights.

  2. Architecture design

    We design how data is split, indexed, searched and passed to the model, taking access rights and privacy requirements into account.

  3. Prototype and evaluation

    We measure answer accuracy and source citation on a test set of your real questions and improve the architecture accordingly.

  4. Rollout and monitoring

    We monitor the system through user feedback and quality metrics and refresh the index as data changes.

Deliverables

  • An assistant design grounded in your data that cites sources
  • An evaluation test set and quality report
  • A data and security architecture that respects access rights
  • An operations and update guide

Frequently asked questions

Does RAG completely prevent hallucination?

No. Grounding answers in your sources reduces the risk of hallucination but does not eliminate it. That is why we set up source citation, behaviour where the assistant says when it does not know, and regular evaluation tests.

Does our data go to the model and outside?

It depends on the architecture. With an Enterprise API only the document passages relevant to a question may be sent to the model; if privacy requirements are high, the model can run inside your organisation (on-premise). In every case we document the data flow.

Let's talk about this service

Let us listen to your processes and goals and evaluate together whether this service fits you.

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