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AI solutions

AI that genuinely saves time and money. Not AI for the hype — every solution has a measurable goal and a purpose within your business process.

Where does AI actually pay off in a company?

AI pays off where a repetitive task has clear inputs and a verifiable output: document and invoice data extraction, answering internal questions from company knowledge, and analysing data for decisions. Each deployment needs a measurable goal and a human confirming the result — otherwise it's AI for the hype.

Where AI makes sense

Golden rule: AI where there are many repetitive inputs and we can judge whether the result is correct. Otherwise a human stays in charge.

Our AI solutions

SolutionWhat it doesTypical impact
Document workflowAI extracts data from invoices, contracts, orders and sorts them−40% manual work, fewer errors
AI assistantAn internal assistant over your data and documentsQuick answers, fewer pointless emails
Analysis & predictionClassification, anomalies, demand forecastsBetter decisions on time
Email processingSorting, routing, reply draftingFaster responses to clients

Measurable impact — example

A real case: deploying AI into document processing over 6 months. The processing time of a single document dropped from 8 minutes to just under 3.

8 → 2.9 minDocument processing time
−40%Manual work saved
6 monthsTime to deploy
Document processing time (min) — deployment progress

How we start with AI

  1. Use-case identification — we pick a process with the most potential that can be validated.
  2. Data readiness — we make sure data is available and sufficient (often via automation and integrations).
  3. Proof of Concept — a small, measurable experiment, not a company-wide rollout.
  4. Deployment and measurement — once validated, we scale into operation with measurement points.
  5. Iteration — we fine-tune based on real data.

Responsibility and control

  • Human in the loop — for critical decisions AI proposes, a human decides.
  • Explainability — we can tell what the AI bases its result on.
  • Data privacy — sensitive data is handled within agreed boundaries and encryption.