A trio of former Apple engineers is leading a new data storage platform for developers building machine learning and artificial intelligence applications.
Seattle-based XetHub emerged from stealth mode Monday and announced $7.5 million in seed funding from Madrona Venture Group.
The company is led by former executives at Turi, a machine learning startup acquired by Apple in 2016 for around $200 million in one of the largest acquisitions for a Seattle startup. Turi founder Carlos Guestrin is advising XetHub.
XetHub aims to help developers speed up how they write and implement code for “intelligent” applications, particularly for teams that are working remotely.
“When Amazon recommends a product, or Gmail auto-suggests an email reply, or Apple’s FaceID unlocks a screen: these are examples of intelligent applications,” said co-founder Rajat Arya. “Up until now, this AI-powered functionality has been limited to those big players, but increasingly we’re going to see every business adopt AI.”
As these applications require more and more data, XetHub is betting that businesses will become more efficient with its tool.
Arya points to Madrona’s IA40 list — described as an index of the “top private companies building with AI that will shape our future” — as evidence of the variety and volume of startups now incorporating intelligent applications into their businesses. XetHub aims to go after this expanding market.
“Developing and deploying these applications is constrained by legacy infrastructure and complex data workflows, and XetHub addresses these pain points from the developer point of view,” Madrona Managing Director Matt McIlwain said in a statement.
XetHub resembles GitHub, a commercial service based on the Git open-source project founded in 2008 and acquired by Microsoft in 2018. GitHub gives users a web-based way to collaborate on software development. Developers upload the code they’ve written to GitHub, opening it up to other developers to track the progress of ongoing projects and maintain completed ones.
XetHub lets engineering teams do something similar, but for data storage alongside code in their Git repository.
Similar to GitHub’s software development tools, the XetHub platform will let machine learning developers collaborate while also providing a “governance record” that tracks any changes made to data.
The company says the platform can currently handle 1TB-sized datasets and plans to increase that amount to 100TB in the near future. It will release a generally available version later in 2023.
The startup is led by CEO Yucheng Low, who worked at Turi as its chief architect for more than three years, then as an engineer at Apple for five years. He is a graduate of Carnegie Mellon University, where he earned a PhD in machine learning.
Arya was Turi’s director of technical sales and became a system software engineer at Apple. He also previously worked at Amazon Web Services and Microsoft.
The founding team is rounded out by Ajit Banerjee, a former senior software architect at Apple. Banerjee co-founded a Seattle job interviewing and matching startup called TalentWorks.
Arya said the Turi team operated “as a startup within Apple” and helped build internal machine learning products.
“We’d find an ML team, deliver value to them quickly, and then iteratively improve,” he said. “Our first service at Apple was a data product, which remains the most widely used offering in Apple’s internal ML platform today.”
Also advising XetHub is Shanku Niyogi, vice president of product at Databricks and former senior vice president of product at GitHub.
The company will mostly target medium-sized businesses and will be free to start. It plans to introduce usage-based pricing, based on dimensions of compute, data storage and data transfer.
The platform, which is going public today, attracted hundreds of signups, all through word of mouth, Arya said. During the six months leading up to the public launch, the company worked with a “handful of teams across a couple industries” to use XetHub through a private beta.
Developers have a variety of existing options when it comes to data storage platforms. XetHub will compete with Git LFS, which offers storage for large datasets inside Git; Iterative.ai, a well-funded collaborative machine learning platform that launched its first product, DVC Studio, in June 2021; and DoltHub, an SQL database that mimics the features of Git.
“However, the key difference is that we are not just addressing machine learning pipelines and reproducibility, but instead addressing the much more fundamental challenge of data collaboration,” Arya said of competition.