AI and automation that reach production

AI solutions used in everyday work, not only in a pilot.

AI applications and automation

Document handling, customer service assistants, search across internal knowledge and forecasting. Before the build we decide how results are evaluated, what a call costs at real volume and where personal data goes. ModelHarbour, our own AI gateway, shows what spending caps and EU mode look like.

Data platforms and reporting

Data warehouses, pipelines, semantic layers and dashboards that get used. The starting point is the decisions you want to change, not a tool, and data quality, lineage and access control are built in from the start.

Governance, ownership and hand-over

Who retrains the model, who owns the prompts and pipelines, what happens if you take it in-house. That is settled from the start, often in a review of your web, IT and AI before anything is built.

Questions we get

We only have a vague idea. Is it too early?

No. Much of the first call is about narrowing a broad ambition down to a use case with a measurable result.

How are GDPR and the EU AI Act handled?

Data storage, legal basis and risk classification are part of the requirements before the build, not discovered at contract stage.