2 min

Thinkwise introduces Automated Machine Learning in the latest version of its enterprise low code platform. Automated Machine Learning allows users without a data science background to add machine learning algorithms to their applications.

Automated Machine Learning (AutoML) allows organisations to easily train machine learning models on historical data and then apply these models to current data all from within the Thinkwise Platform. By defining the relevant data and the desired predictions, this automatically produces data-driven insights.

The Thinkwise Platform already offers possibilities for calculating cost prices or optimising logistics processes, but for genuinely complex predictions they now use AutoML. Organisations can train machine learning models using existing business data. Users can follow an online manual to set up, train and apply a machine learning model.

For example, it is possible to predict the priority of a support ticket or the customer rating of a product or service. With AutoML, it is also possible to predict numerical values such as the lead time of a project or the estimated project budget. The use of machine learning is highly suitable for these calculations due to the many factors involved. AutoML automates this process and integrates seamlessly into the Thinkwise Platform.

Jasper Kloost, CTO of Thinkwise, is pleased with the addition of AutoML to the Thinkwise Platform. “Machine learning normally requires in-depth knowledge of mathematics and statistics, but now any developer can use this technology with our low-code platform.”

Other additions

In addition to Automated Machine Learning, the new version 2020.2 of the platform also offers users various improvements in terms of usability and license management, as well as simplified deployment of applications in cloud environments.

The company already started the development of version 2021.1. The plan is to introduce a complete dashboard for remote monitoring of Thinkwise applications. In addition, the company plans on introducing Natural Language Understanding to the platform, which will make it possible to request data or get tasks done in applications with natural language.