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ARTIFICIAL INTELLIGENCE

FIG. 02 — AI

AI is a component, not a product. To be useful it has to be connected to your own data, your own rules and an output you can verify. Making that connection is the work.

WAYS OF WORKING

  • 01 Fixed-scope project A new product, a defined module, a rebuild
  • 02 Team augmentation Companies with their own team that need temporary capacity
  • 03 Assessment and audit Before a decision, before a takeover, or on a stalled project

01 SCOPE

WHAT YOU GET.

We connect language models to real workflows: document search, automation, assistants.

  1. INTERNAL ASSISTANT

    Question and answer over your own documents. Answers cite their source; a RAG architecture keeps invention down.

  2. DOCUMENT PROCESSING

    Structured data pulled out of invoices, contracts and forms, then written into the system you already use.

  3. WORKFLOW AUTOMATION

    Automation of repetitive text work: classification, summarising, drafting, routing.

  4. COST AND PRIVACY

    We decide up front which data may leave the building. Where needed we run local models or an on-premise install.

02 FLOW

Architecture behind a sourced answer 01 Question 02 Vector search 03 Your documents 04 Language model 05 Sourced answer Architecture behind a sourced answer 01 Question 02 Vector search 03 Your documents 04 Language model 05 Sourced answer

03 OTHER SERVICES

04 CONTACT

LET'S WRITE THE SCOPE.

Describe the need in a few sentences. In the first call we work out the scope and a rough budget together.

A few sentences on what you want to build; add a timeline and budget range if you have one.

BEFORE THE CALL