Sematic secures $3M round for its ‘continuous’ ML platform

Categories Edge Computing News  |  Edge Startups  |  Funding
Sematic secures $3M round for its ‘continuous’ ML platform

Sematic, an open-source continuous machine learning platform provider, has announced it received $3 million in seed funding. With this new funding, the company plans to accelerate its hiring process, launch cloud-based solutions and attract more engineers to use their machine learning platform. Since Sematic’s launch in August 2022, it has closed a commercial agreement with Voxel, an AI-powered workplace safety platform. The company says its continuous ML platform is being increasingly adopted by the open-source community.

Race Capital led the funding round with participation from Y Combinator, Soma Capital, Leonis Capital and Pioneer Fund. There were several angel investors, including Brandon Leonardo, co-founder of Instacart, Oliver Cameron, VP of product at Cruise and Jeremy Stanley, former VP of data science at Instacart and co-founder of Anomalo.

“Sematic is exactly the kind of machine learning platform we want at Voxel. It gives my ML team unparalleled visibility into our ML pipelines and just the right level of abstraction for us to focus on business logic and leverage cloud resources without requiring infrastructure skills,” said Anurag Kanungo, CTO and co-founder of Voxel.

The Sematic continuous machine learning platform helps companies to automate, schedule and clone pipelines whenever a new labeled dataset is available. Semantic offers companies the ability to expand their machine learning teams so they can focus on creating new models without having to worry about automation infrastructure upkeep, the company says. According to one Gartner forecast, AI-derived business value is forecast to reach $3.9 trillion in 2022.

“Data is the new oil and Sematic is building the new oil rig for the ML engineer team,” said Alfred Chuang, partner at Race Capital. “Today, ML engineers heavily rely on their infrastructure team for testing, automation, and deployment of ML models. This is a crucial problem whose solution will push the entire data and machine learning industry forward.”

What is a continuous learning ML platform?

According to Sematic, continuous learning is an automated recurrent end-to-end machine learning pipeline that enables regression testing and continuous performance. That said, Semantic teams believe there is a large disparity between the hypothetical potential of machine learning and its actual implementation. They state that the principal explanation for this is the discrepancy between the existing tools and the ML workforce’s expectations.

For example, the founding team at Cruise spent four years building machine learning infrastructure for the robotaxi company. They hired dozens of machine learning engineers to reduce the complexity of large-scale cloud infrastructure. However, not all companies and enterprises can afford this expense.

“I want to democratize access to continuous machine learning. Not all businesses can afford to hire dozens of ML Infrastructure engineers like we did at Cruise. My team and I are building Sematic as the go-to open-source ML platform for companies of all sizes. Safety and accuracy of machine learning models and empowering ML teams to move much faster is our mission,” said Mr. Turlay, CEO of Sematic.

Article Topics

 |   |   |   | 

Comments

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Featured Edge Computing Company

Edge Ecosystem Videos

Machine learning at the Edge

“Barbara

Latest News