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AI automation and adoption AI that helps your team get work done.

We find tasks worth improving, design practical automations and help your team adopt new ways of working. We start with one process, not with buying tools.

Let’s find your first use case
For whom
For teams trying AI on individual tasks, with no shared way of working or ground rules.
What the work can include
Choosing the first use case, a pilot, automation, working rules and team training.
Stages
Diagnosis → Plan → Pilot → Measurement → Next iteration

When this helps

Signs your team’s use of AI needs shared rules

  • Everyone on the team uses a different AI tool, and nobody knows what comes of it.

  • The same manual tasks come back every week and eat into time for more important work.

  • We want to adopt AI, but we don’t know where to start or how to do it safely.

Scope

What the work can include

Depending on your goal and how ready your team is, the work may include:

Process review
We map how a chosen task works today: who does it, with what data and where most time is lost.
Choosing the first use case
We assess each idea for its benefits, risks and data availability, then pick one that can be tested in practice.
Pilot
We test the solution on a limited scale against criteria set in advance: what counts as success and what signals a change of course.
Automation and integrations
We connect the tools your business already uses – where that’s possible and makes sense.
Rules and oversight
We agree which data can go into AI tools, who has access and at which points a person checks the output.
Team training
We show the people who’ll use the solution how to work with it and how to report problems.

Note: The exact scope is agreed after the diagnosis. Tool licences and fees, custom builds on a specific technology, and ongoing maintenance after the pilot aren’t included by default. If you need them, we’ll discuss them separately.

Stages

From a first use case to everyday work

  1. Diagnosis

    We talk to the people who actually do the work. We look at processes, data, tools and constraints, such as confidentiality requirements.

  2. Plan

    We choose the use case, an owner on your side, the success criteria and the points where a person checks the output.

  3. Pilot

    We run the solution on a limited scale and collect feedback from the team as they work with it.

  4. Measurement

    We compare the situation before and after the pilot: time per task, number of errors, share of outputs accepted without edits.

  5. Next iteration

    We decide together: refine the solution, extend it to more tasks or end the test.

Let’s find your first use case

Outcomes

What you get and how we track progress

Possible deliverables

  • a description of the chosen process as it works today
  • a use‑case description with success criteria
  • a working pilot on a limited scale
  • rules for using AI: data, access, oversight
  • training materials for your team
  • a pilot summary with recommended next steps

Measures we use

  • time needed to complete the task, before and after the pilot
  • how often errors and corrections occur
  • share of outputs accepted without changes
  • whether the team actually uses the solution in its daily work

We measure a baseline before the pilot and agree the criteria with you. We don’t assume in advance how much time you’ll save – only the test will show that.

Questions

Questions about AI adoption

Which workflows should be automated first?

The best place to start is with tasks that come up often, follow fixed rules and carry little risk if something goes wrong. The process also needs an owner and data you can work with. Tasks that call for judgement, empathy or legal responsibility stay with people, or AI plays only a supporting role.

What about data security?

Before anything goes live, we agree which data can go into AI tools and which can’t. We take into account your company’s own policies and the privacy settings of the tools in question. If the process involves sensitive data, we design the pilot so that it either doesn’t use that data or uses it only within agreed limits.

What happens after the pilot?

The pilot ends with a summary and recommended next steps. Your team gets the rules and materials it needs to work with the solution independently. Further support and maintenance, if needed, are agreed separately.

Let’s start with one task

Describe a task that takes up a lot of your team’s time or that you have doubts about. We’ll look at whether AI makes sense there.

Let’s find your first use case