Baseten Gives Data Science and Machine Learning Teams the Superpowers They Need to Build Production-Grade Machine Learning-Powered Apps -…

Baseten formally launched with its product that makes going from machine learning model to production-grade applications fast and easy by giving data science and machine learning teams the ability to incorporate machine learning into business processes without backend, frontend or MLOps knowledge. The product has been in private beta since last summer with well-known brands that have used it for everything from abuse detection to fraud prevention.It is in public beta at this time.

Its clear that the performance and capabilities of machine learning models are no longer the limiting factor to widespread machine learning adoption instead, practitioners are struggling to integrate their models with real world business processes because of the enormous engineering effort required to do so. With Baseten, were reducing this burden and accelerating time to value by productizing the various skills needed to bring models to the real world, said Tuhin Srivastava, co-founder and CEO of Baseten.

Over the last decade, theres been enormous progress in advancing the capabilities of machine learning, driven primarily by new model architectures and the ever-decreasing cost of compute. But the critical step of integrating models with real-world business processes is still a lengthy, expensive process that prevents the majority of businesses from seeing a return on machine learning investments. While a typical machine learning model may take just a few weeks to train, building the infrastructure, APIs and UI so that the model can be used by businesses can take more than six months and requires additional resources in the form of MLOps, backend and frontend engineers.

This is a problem that Basetens co-founders Tuhin Srivastava (CEO), Amir Haghighat (CTO) and Philip Howes (Chief Scientist) encountered first hand at Gumroad. There Haghighat was the head of engineering and Srivastava and Howes were both data scientists who had to learn to become full-stack engineers so they could use machine learning to detect fraud and moderate content. The systems they built at Gumroad are still in use and have screened hundreds of millions of dollars of transactions to date.

The trio founded Baseten so that data scientists dont have to learn to become full-stack engineers in order to build web applications for their machine learning models. Baseten lowers the barrier to usable machine learning by enabling data science and machine learning teams to incorporate their machine learning models into production-grade applications within hours instead of months. With Baseten, data science and machine learning teams can easily serve their models, build backends and frontends and ship applications that solve critical business problems including operations optimization, content moderation, fraud detection and lead scoring.

Customers on Baseten:

Analysts on Baseten:

Baseten Raises $20 Million in Seed and Series A Funding

Baseten also announced that it has raised $8 million in seed funding co-led by Greylock and South Park Commons Fund and $12 million in Series A funding led by Greylock. Baseten is using the funding to expand its engineering and go-to-market teams.

Greylock General Partner and Baseten Board Member Sarah Guo said: Despite the broad understanding that AI has the capability to revolutionize business, most organizations struggle to drive real ROI from theirmachine learning efforts, stymied by the high upfront investment required. Baseten radically reduces the time, specialized expertise, cost and cross-team coordination required to successfully ship machine learning apps to production. Its end-to-end platform frees data science and machine learning teams from grunt work and empowers them to spend more time innovating and iterating to maximize impact. The Baseten team has experienced this pain first-hand, and that authenticity and care shows in the solution theyve designed. Were thrilled to partner with them to democratize access to the revolution in machine learning.

Other participants in the seed round include AI Fund, Caffeinated Capital and angel investors Lachy Groom (ex-Stripe), Greg Brockman (co-founder and CTO of OpenAI), Dylan Field (co-founder and CEO of Figma), Mustafa Suleyman (co-founder of DeepMind) and DJ Patil (ex-Chief Data Scientist of the United States Office of Science and Technology Policy).

Other participants in the A round include South Park Commons and angel investors Lachy Groom, Cristina Cordova (ex-Stripe), Dev Ittycheria (CEO of MongoDB), Jay Simon (ex-President of Atlassian) and Jean-Denis Greze (CTO of Plaid).

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Baseten Gives Data Science and Machine Learning Teams the Superpowers They Need to Build Production-Grade Machine Learning-Powered Apps -...