IS Predict is a proven solution provider for self-learning and explainable Artificial Intelligence. Clients are automotive, automotive suppliers, discrete manufacturing, process industry, as well as providers of IT and financial services.

Cost reductions are achieved in reducing minor quality in production, reducing energy / CO2, reducing machinery stand stills, optimizing logistics and minimizing risks for problems in operation of IT service providers as well as minimizing risks for credit loss at banks.

Easy Engineering: What are the main areas of activity of the company?

IS Predict: Data analytics in various industrial branches. It covers predictions, anomaly detection, what-if simulations, recommendations for operators and subject matter experts as well as automated control of machinery and processes.

E.E: What’s the news for 2021 about new products?

IS Predict: Our Artificial Intelligence solution works with semantical deep networks: This is like Deep Learning, but not with Neuronal Networks because they do not give transparency on root-cause, on why things are happening and why AI recommends this or that.

This transparency is always important for us humans to understand and trust complex data analytics.

In addition, we improved our self-learning algorithms which partly automate data science tasks. In this way, AI becomes scalable because dependencies on Data Science experts are reduced.

E.E: What are the ranges of products?

IS Predict: We have solutions for different analytical challenges (see answers in question 1).

For this, we have developed the following AI software modules: Data Pattern Discovery, Self-Learning Analytics, Prediction, Anomaly Detection, Root Cause Analytics, Simulation and Predictive Control.

E.E: At what stage is the market where you are currently active?

IS Predict: At B2C, AI is already widely used. When you talk to your smart watch, when you use advanced features in new smart cars.

At B2B, it differs significantly from the industrial branche.

We are mainly operating at corporate level, meaning small medium enterprises do not yet invest in Industry 4.0 or in Artificial Intelligence.

Forerunners are production companies, like automotive, automotive suppliers, chemical companies and building companies.

E.E: What can you tell us about market trends?

IS Predict: More and more data is gathered. Companies have started building data lakes. The consequent next step is that the data gives value for improving business.

Here, AI is more and more used. However, AI needs to be good not only for now, but also for the next few months and years.

Thus, there are 2 possibilities:

  • Either companies build up their own Data Science team to always make sure that running AI solutions do not lose their value.
  • Or companies implement adaptive AI solutions where AI automates those tasks of adapting AI solution.

If there are many changes in the processes, i.e. due to high variance or dynamic influencing factors, then, on the long run, only the 2nd way is reasonable and scalable.

E.E: What are the most innovative products marketed?

IS Predict: AI solutions are at the beginning. Thus, they are – more or less – all innovative. (Some companies declare they have „AI inside” their products, but it actually is normal mathematics, like statistics. Of course, statistics is not bad and can be sufficient for analytical tasks. But it has nothing to do with AI.)

As mentioned above, it is important that AI solutions do not only give value now, but also in a few years along the line.

Therefore, adaptiveness and self-learning is relevant. For sure, it is not easy to realize this. But investment should be done for long value-add. Therefore, self-learning and adaptiveness are most innovative analytics on the market, also in addition with so-called Explainable AI.

E.E: What estimations do you have for 2021?

IS Predict: Well, 2021 is over, soon.But I believe that AI will be more and more important across industry. Of course, corporate companies having more innovation budget and investing more in new technology than small medium enterprises.

Thus, in the future, it will not be „wow, you have AI implemented, already” but rather be „ups, you have not yet started activities to evaluate AI in your business”.