Machine Learning Experimentation Platform Raises $4.5 Million In Funding

by NeoTech Post
Machine Learning Experimentation Platform Raises $4.5 Million In Funding, a machine learning experimentation platform that enables data scientists to track, compare, monitor, and optimize model development, raised $4.5 million in funding.

Investors include Trilogy Equity Partners, Two Sigma Ventures, and Founder’s co-op. 

The company plans to use the new funds to expand Comet Enterprise and continue bringing meta learning capabilities to the market.

Since the launch of in 2018, millions of models have been trained using the platform across multiple industries, spanning autonomous vehicles, financial services, technology, bioinformatics, satellite imagery, fundamental physics research, and much more.

The company’s customers include Ancestry, General Electric, The National Institute of Health, Boeing, Google, and Uber.

“Professionals from the best companies in the world choose Comet, which allows them to build ML models that bring significant business value. In such a fast-growing space, Comet is well-positioned to become the de-facto Machine Learning development platform. As someone who led Microsoft’s developer tools division, I’m excited to see Comet follow a similar growth trajectory,” said Yuval Neeman, partner at Trilogy Equity Partners. 

The company recently announced two partnerships. The first with Uber AI to extend Ludwig, a low-code deep learning toolbox, to support the platform. The second with Dell EMC, allowing users to leverage the Dell EMC reference architecture with Comet. 

“We founded Comet with the goal of helping companies gain business value from machine learning. With Comet Enterprise, data scientists can build reliable models faster and organizations can gain visibility into their AI/ML efforts and progress,” said Gideon Mendels, Co-founder/CEO, “Comet Enterprise already supports some of the biggest and most impactful machine learning teams in the world, and we plan on helping more organizations do the same.” 

Image by Pete Linforth from Pixabay