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Less manual work in marketing and sales

AI automation

AI automation pays off when it is tied to work your team already does. We find the tasks that take the most time, build automated workflows for them and put a checkpoint wherever a person needs to approve the result.

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Interlocking brass and steel gears on a pale workbench
Implementation
2–6 weeks

What automation should give you

We start with one or two workflows where the gain is easy to measure, and extend from there. The AI readiness assessment is a quick way to see where your business stands before we talk.

  • Less manual work in marketing and sales processes.
  • Faster content production, follow-up and reporting.
  • More consistent quality, because routines and checks are built in.

What you get

Each of these is a document or a setup your team can use, handed over in order of priority.

  • Automation audit

    A prioritised list of what is worth automating.

  • Workflow design

    How each automated process runs, and who owns it.

  • AI agent setup

    Agents and prompts for content, data and routine tasks.

  • Integrations

    Connections between your tools and data sources.

  • Documentation

    How the system is run, and how your team uses it.

  • Performance report

    Time saved, errors caught and what to automate next.

Also covered

  • Process mapping and prioritisation
  • Workflow design and build
  • CRM integration and lead scoring
  • AI assistants and chatbots
  • Email automation
  • Automated reporting
  • Alerts and escalation
  • Quality checks and approval steps
  • Documentation and training
  • Ongoing improvement of workflows
How it works

How an engagement runs

We work in short iterations and keep a log of what we tested, so you can follow every decision.

  1. Step 1: Find the workflows to automate first

    We map which tasks take the most time, where errors happen and which workflows would give the quickest gain if they were automated.

    • A review of the tools and routines you have today
    • Priorities set by effect and complexity
    • A clear implementation plan

  2. Step 2: Build the automation, with checkpoints

    We set up automated processes for lead handling, content work and reporting on the tools you already use, from simple Zapier flows to custom AI agents.

    • Integrations between CRM, ad platforms and analytics
    • Automatic alerts and tasks
    • Manual approval where the output needs a person’s judgment

  3. Step 3: Keep it running, and improve it

    We monitor the workflows, update the logic when something changes and document everything, so your team can rely on them.

    • Monitoring and error handling
    • Continuous improvement of prompts and rules
    • Documentation and training for the team

Want a rough number first?

The free calculator gives you an estimate in a couple of minutes, before you talk to anyone.

Take the AI readiness assessment

AI automation and traditional automation: what is new?

Traditional automation follows fixed rules: if X happens, do Y. It works well for repetitive tasks with clear logic, such as sending a welcome email when someone signs up.

AI automation adds a step that can read and judge. It can interpret unstructured text and make a decision based on context. That lets a workflow handle harder tasks, such as scoring a lead from the content of an email or writing a report adapted to its reader.

In practice we use both: rule-based automation for the predictable steps, and AI where the step needs judgment, drafting or interpretation of data. Typical examples are lead scoring and email follow-up for B2B companies, and abandoned-cart emails and reporting for online stores.

Questions we often get

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What kinds of tasks can be automated?

Content production, reporting, data entry, lead routing, email sequences and social media posting are the most common. We start with the tasks where the gain is large and the risk is low.

Do we have to change tools?

Usually not. We build on the tools you already have as far as possible, and only recommend a change when the gain is clear.

Do we need technical knowledge?

No. We handle the setup and write the documentation. Your team uses the finished workflows through the tools they already know.

How quickly can we get started?

Many projects start with a pilot delivered in 2–4 weeks, before we extend it to more workflows. The setup is quoted as a standalone project in euros, and you see the full cost before anything starts.

Is AI automation safe, and how do you keep quality up?

Yes, with access control, logging and checkpoints in place. Every automation has validation steps and points where a person reviews the result. We test before anything goes live and monitor it afterwards.

Often combined with

Which services belong together depends on the business. The industry pages show the mix we use for each sector, and the case studies show the work clients have agreed to publish.

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