Continual, a startup that focuses on simplifying operational AI on top of a modern data stack, today announced that it has raised a $14.5 million Series A funding round led by Innovation Endeavors. In addition, the company today announced that its cloud platform is now generally available.
The company, which focuses its AI efforts on predictive models for things like inventory forecasts, risk mitigation and supply chain logistics, previously raised a $4 million seed round, which it announced last December. Other investors in this new round include Amplify Partners, Illuminate Ventures, Inspired Capital, Data Community Fund, Activation, New Normal, GTMfund, as well as angels Tomer Shiran (founder of Dremio) and Tristan Handy (founder of dbt Labs).
Image Credits: Continual
Enterprises now own massive amounts of data but it remains difficult for them to take this information, which typically sits in a data warehouse like Snowflake or AWS Redshift and turn it into predictive models. The idea behind Continual is to allow them to do this without having to reinvent the wheel. The service isn’t a low-code/no-code tool but it does put an emphasis on making its features accessible in that it allows data teams to leverage skills they already have — like SQL and dbt — to quickly build AI models and put them into production.
Looking ahead, Continual will add some more advanced features, too. “To better support advanced users, we’re adding support for machine learning engineers to extend Continual’s automated machine learning engine with custom models and then expose these new capabilities to all users in their organization,” the company’s CEO and co-founder Tristan Zajonc explained. “We ultimately see Continual as being powered by an ecosystem of AI capabilities both developed internally and externally.”
One of these advanced features is the ability to extend Continual’s MLOps service with custom capabilities, which is now available in preview. But the company also has quite a few more of these more advanced features in the pipeline. Continual also plans to launch new automated feature engineering capabilities to simplify the machine learning workflow, for example. And later this year, the company also plans to introduce support for real-time feature and model serving, something its customers have been asking for.
Zajonc noted that just in the last three months, the company managed to double the number of active users and deployed models, as well as its booked annual recurring revenue. Those are obviously numbers that make VC’s perk up their ears, so it’s maybe no surprise that Continual was able to raise this new round so soon after its seed funding.
“Over the last few years, we’ve seen predictive analytics and AI become the lifeblood of today’s leading enterprises,” Harpinder (Harpi) Singh, partner at Innovation Endeavors. “But most companies still struggle to infuse AI broadly in their organizations. We believe Continual’s approach to building directly on an organization’s existing cloud data platforms and empowering all user types, not just machine learning engineers, is the right recipe to unlock the potential of AI for every organization.”
Now, the plan is to double the team by the end of 2022 to support all of these new customers and build these new advanced features.