Robert van der Linden, founder of Thinkwise. It is no secret that Thinkwise offers a unique product in the low-code landscape. Forrester research...
Thinkwise introduces Automated Machine Learning in the latest version of its low-code platform
Apeldoorn, 2 July 2020 – Thinkwise has introduced the latest version of its enterprise low-code platform. The most important addition is Automated Machine Learning, which enables users, who do not have a data science background, to add machine learning algorithms to their applications. Organizations can benefit from automated data-driven insights and directly apply them in their business processes.
Since Thinkwise made the transition from software developer to platform supplier the development of the low-code platform has rapidly gained momentum. Since February of this year, no less than 80 suggestions and ideas from the Thinkwise Community have been included in version 2020.2 of the Thinkwise Platform. Furthermore, users of the platform benefit from several improvements with regard to ease of use and existing functionality, the management of licenses and the roll out of applications in cloud environments, which has also become much easier.
The most notable new functionality however is Automated Machine Learning (AutoML). From the Thinkwise Platform, organizations can train simple machine learning models based on historical data and subsequently apply these models to current data. By defining the relevant data and the desired prediction, this delivers automated data-driven insights, that improve over time.
“We are extremely proud to be able to make AutoML fully available to users of the Thinkwise Platform,” says Jasper Kloost, Thinkwise CTO. “Machine learning normally requires in-depth knowledge of mathematics and statistics, but now every developer can use this technology with our low-code platform.”
The Thinkwise Platform already offers extensive features for activities such as the automatic calculation of cost prices or the optimization of logistic processes, as standard functionality. AutoML now offers a solution for more complex predictions based on large volumes of data. Organizations can train machine learning models, directly from the Thinkwise Platform, on the basis of their existing business data and low-code models, and subsequently apply these models to new data.
This makes it possible, as examples, to predict things such as the priority of a support ticket, the risk category of a quotation or the customer review of a product or service. Numeric values can also be predicted such as the estimated costs of a project or service, the cost price of a product based on a recipe, or the lead time of a project. Machine learning is extremely suitable for these types of calculations because they depend on many combinations of factors. AutoML automates this process and also integrates seamlessly in the Thinkwise Platform, so that it can optimally benefit from the specified low-code models.
“Right from the start of Thinkwise it has always been our objective to eliminate the technical challenge from software development,” says Robert van der Linden Thinkwise CEO. “With this new release of our platform we simplify machine learning and it can now be applied by everybody in the Thinkwise Platform.”
Roadmap to 2021
Despite the new release, the Thinkwise team is not resting on their laurels and has already started with the development of version 2021.1 of the platform. This will be available before the end of this year and offer various improvements that will make life far more enjoyable for developers at ISVs, customers and partners, including a complete dashboard for the remote monitoring of Thinkwise applications. In addition, the Upcycler, the popular technology used to modernize legacy applications, will be fully integrated into the Thinkwise Platform with this version. Thinkwise also expects to introduce Natural Language Understanding in the platform as part of this version. This makes it possible, for example, to request information or execute tasks in applications using natural language.