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Begin using AI.

Get started with AI with a "Proof of Intelligence"

Have you been thinking about how to get started with AI in your organisation? We can help you test how the implementation of machine learning will change and automate your business processes, how your employees will work with it, and if there’s a future for AI in your business.

Proof of Intelligence

/pruːf ɒv ɪnˈtɛlɪʤəns/

Evidence deriving from an experiment or pilot project, which demonstrates that introducing intelligent software in an organization is feasible. It verifies that applying Artificial Intelligence has practical potential.

What are the steps we take together?

  1. Step 1

    Research your processes

    To make sure that when we’re done, your process is effectively supported or replaced by AI, we need to make sure that we’re doing the right things. That’s why we always first research your process as it stands.

  2. Step 2

    Propose improvements

    With some fresh perspective we offer you alternatives to reach your goals, independently of how your process is currently set up. We do this to make sure that we only focus on the necessary steps of the process.

  3. Step 3

    Record decision-making

    When it comes to AI, growing means recording. We map your decision-making steps and make sure everything is properly recorded and stored so that in the future, your decisions can be automated even better.

  4. Step 4


    Good planning results in good execution. With the knowledge of all the previous steps, we create an API and dashboard with functional AI components that you can use to automate or enhance parts of your business processes.

  5. Step 5

    Make sure it works

    After implementation, we check in with you after a couple of months to see whether your suite of tools still suits the process and whether we can move forward with more elaborate AI, using the data we’ve recorded about your decision making.

We've done this before

Ruler case study

Processing legal texts for efficiency.

Learn more about this case
Toptaal case study

Predicting chances of success.

Learn more about this case
What suits my automation purpose?

Pre-trained or custom models?

Deciding on the right tools for the job is a challenge. That’s why we created an overview of the pros and cons of different options you have for implementing AI models in your organisation.

Read on
Do your ambitions match your budget?

What's the budget for building your AI models?

Within 2 minutes we can help you understand what the impact of different choices in technology, responsibility and longevity is on the budget for your AI model.

Calculate the budget for my AI model
Things we've learned along the way about applying AI models.

Our top 5 tips for applying pre-trained AI models.

Peter Peerdeman

Make sure the model is appropriate

Peter, CTO at Lifely

When using pre-trained models, it’s very important to make sure that the pre-training that has been conducted is done on appropriate data, so that you can immediately work with it, without too much hassle. Things to look out for when dealing with text data is that the training set was in the right language and that the characteristics of the texts are somewhat the same as the texts you will put in.

Read our 5 tips

Let's talk AI, get in touch

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