As we get further along in the new way of working, the new normal if you will, finding more efficient ways to do just about everything is becoming paramount for companies looking at buying new software services. To that end, Comet.ml announced a $4.5 million investment today as it tries to build a more efficient machine learning platform.
The money came from existing investors Trilogy Equity Partners, Two Sigma Ventures and Founder’s Co-op. Today’s investment comes on top of an earlier $2.3 million seed.
“We provide a self-hosted and cloud-based meta machine learning platform, and we work with data science AI engineering teams to manage their work to try and explain and optimize their experiments and models,” company co-founder and CEO Gideon Mendels told TechCrunch.
In a growing field with lots of competitors, Mendels says his company’s ability to move easily between platforms is a key differentiator.
“We’re essentially infrastructure agnostic, so we work whether you’re training your models on your laptop, your private cluster or on many of the cloud providers. It doesn’t actually matter, and you can switch between them,” he explained.
The company has 10,000 users on its platform across a community product and a more advanced enterprise product that includes customers like Boeing, Google and Uber.
Mendels says Comet has been able to take advantage of the platform’s popularity to build models based on data customers have made publicly available. The first one involves predicting when a model begins to show training fatigue. The Comet model can see when this happening and signal data scientists to shut the model down 30% faster than this kind of fatigue would normally surface.
The company launched in Seattle at TechStars/Alexa in 2017. The community product debuted in 2018.
Yhat founders Greg Lamp and Austin Ogilvie were working with a team of data scientists at OnDeck, a successful small business loan startup, when they noticed a problem.
Dataiku, a French startup that makes software to help teams of data scientists process and make sense of big data, announced €3.2M in Series A funding today — that’s approximately $3.6M USD. Alven Capital and Serena Capital jointly led the round. The company’s product is called Data Science Studio, which provides soup-to-nuts services for data science teams. The software…