Unveils Pay-As-You-Go AI Management Platform on Google Cloud MT co-founders, from left to right: Tuncay Isik (CEO), Florian Laroumagne (data scientist), Nicolas Gaude (CTO), Pierre Nowak (Senior DevOps) has announced the launch of its AI Management Platform on Google Cloud, allowing businesses with limited resources and infrastructure to now support sophisticated artificial intelligence (AI) initiatives.

The feature-rich platform democratizes AI by eliminating onerous license costs that may cost businesses hundreds of thousands, if not millions of dollars each year. The easy interface would help users to design, deploy, monitor, and retrain models in a few clicks, allowing teams to deliver projects quicker. intends to break down the hurdles that prevent businesses from developing a comprehensive, high-impact AI practice by managing the intricacies across the AI lifecycle and delivering unique pay-as-you-go pricing.

The startup was founded in 2016 by four data scientists who wanted to make it easier for business clients, data scientists, IT experts, and developers to collaborate on AI business applications. To date, it has received $7.5 million in investment.

“We started with the goal of improving the lives of people who work with data day in and day out,” said Tuncay Isik, co-founder and CEO of “Our industry-first AI management platform removes production inhibitors while still scaling the value, domain expertise, and impact users can have at their organizations. By putting our platform in the hands of users via the relationship with Google Cloud, it will shine a whole new light on the way predictive analytics can – and should – be done.”’s AutoML Engine, a Google Cloud Partner Advantage member, provides businesses, data scientists and analysts with all of the tools they need to design, deploy, monitor, and manage data models across a number of industries in one location. would offer an almost limitless range of services that data teams can modify to match business needs, from predictive maintenance to fraud detection and warehouse efficiency.

“Practitioners in our field are bogged down by endless meetings to maintain models once they have been deployed and are in active maintenance mode,” said Nicolas Gaude, co-founder and CTO of provides them a highly customizable platform for monitoring and ensuring their models are on the right track to perform. We feel this is going to open up so many doors in data science that have yet to be explored. Whether you build your model with our industry-leading AutoML engine or bring your own, will simplify your process so you can finish strong.”