Imagine Artificial Intelligence (AI) as the finished car that can drive itself. Machine Learning (ML) is the engine in this car. It is the specific technology that allows the car to learn from experience (data) without being explicitly programmed for each individual corner. Most of the practical AI solutions that we build for medium-sized businesses in Berlin today are based on machine learning. So we use the “engine” to build a “car” for your specific problem.

This is the reality in 9 out of 10 companies and is not an obstacle, but the starting point. An essential part of every AI project is the phase Data preparation. We help you bring together your relevant data from the various silos, clean it up and put it into a usable form. This process is often a huge benefit because it creates transparency about your own data for the first time. The myth of “perfect data” should not be a reason not to embark on the journey to AI.

A PoC is a clearly defined sprint, usually over 4-8 weeks. Step 1: We define a single, measurable question (e.g. “Can we predict machine failures 24 hours in advance?”). Step 2: We collect and analyze the necessary historical data. Step 3: Our data science team develops and trains an initial, prototype machine learning model. Step 4: We present you the results: the accuracy of the predictions and a clear calculation of the potential ROI. The result is not finished software, but a well-founded go/no-go decision for the main project in Berlin.