OutSystems targets AI adoption challenges with Machine Learning Builder

While there is a growing awareness of the benefits of artificial intelligence to businesses, there are a number of challenges for companies that want to implement AI, such as accessing data science talents and understanding use cases.

In order to fill this gap, application development platform provider OutSystems Inc. launched its Machine Learning Builder, which allows companies to interact with several machine-learning models and put them into production in just a few days.

“This essentially speaks to the fact that a lot of companies do not have access to data science talent; they really struggle to adopt machine learning,” said Antonio Alegria (pictured), head of AI at OutSystems. “We’re also increasing the productivity for customers to implement AI and machine learning. We use partners behind the scenes and cloud providers for the core technology, with automated machine learning and all of that.”

Alegria spoke with Stu Miniman, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the NextStep 2020 event. They discussed how OutSystems is injecting AI into its products, the capabilities of its new Machine Learning Builder, and the trend toward democratization of AI services. (* Disclosure below.)

Strategies are complementary

OutSystems has two complementary visions and strategies for AI, according to Alegria. “One of them is we really want to improve our own product, improve the automation in the product … by using AI together with great user experience and the best programming language for software automation,” he explained.

As part of that strategy, OutSystems first introduced its AI Assistant to its software development environment. After significantly accelerating automation at this stage, promoting a frictionless experience during the coding process, the company started to infuse AI into its products and across the software development lifecycle.

“We took this core technology that we use to guide developers and assist and automate their work, and we use the same capability to help developers, tech leads and architects to analyze the code,” Alegria pointed out.

The second AI strategy is to help customers themselves to use AI and machine learning in their own applications — and for that purpose the Machine Learning Builder was created.

“So developers can essentially just pick the data they have already inside the AI systems platform, and they want to just select ‘I want to train this machine learning model to predict this field,’” Alegria explained. “It runs dozens of experiments, selects the best algorithms, transforms the data for you without you needing to have a lot of data science experience. And then you can just drag and drop into platform, integrate in your application, and you’re good to go.”

For AI and machine learning that are integrated with OutSystems products for automation, validation and guidance, there are no extra costs for customers, as these are a kind of “core building block” for the services offered, according to Alegria.

“For machine-learning services and components that customers can use in their own applications, we allow you to integrate with cloud providers and the billing is done separately,” he concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the NextStep 2020 event. (* Disclosure: TheCUBE is a paid media partner for NextStep 2020. Neither OutSystems Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE