This distributed data storage startup wants to take on the Big Cloud

The explosion of AI companies has pushed the demand for computing power to new extremes, and companies like CoreWeave, Together AI, and Lambda Labs have capitalized on this demand, attracting massive amounts of attention and capital for their ability to deliver distributed computing capacity.

But most companies still store data with the big three cloud providers, AWS, Google Cloud, and Microsoft Azure, whose storage systems are designed to keep data close to their computing resources, not spread across multiple clouds or regions.

“Modern AI workloads and AI infrastructure are opting for distributed computing over large clouds,” Ovis Tariq, co-founder and CEO of Tigris Data, told TechCrunch. “We want to provide the same option for storage, because without storage, compute is nothing.”

Tigris, founded by the team that developed Uber’s storage platform, is building a network of local data storage centers that it claims can meet the distributed computing needs of modern AI workloads. The startup’s native storage platform “moves with your compute, (allows) data to automatically replicate to where the GPUs reside, supports billions of small files, and provides low-latency access for training, inference, and proxy workloads,” Tariq said.

To do all this, Tigris recently raised a $25 million Series A round led by Spark Capital and saw participation from existing investors, including Andreessen Horowitz, TechCrunch has learned exclusively. The startup is going against incumbents, which Tariq calls “the big cloud.”

Tariq feels that these employees not only provide a more expensive data storage service, but also provide a less efficient service. AWS, Google Cloud, and Microsoft Azure have historically charged an exit fee (called a “cloud tax” in the industry) if a customer wants to move to another cloud provider, or download and move their data if they want, for example, to use a cheaper GPU or train models in different parts of the world simultaneously. Think of it like having to pay extra for your gym if you want to stop going there.

According to Batuhan Taskaya, head of engineering at Fal.ai, a Tigris customer, these costs previously accounted for the majority of Fal’s cloud spending.

Aside from egress fees, Tariq says there is still a latency issue with larger cloud providers. “The exit fees were just a symptom of a deeper problem: centralized storage that couldn’t keep up with the high-speed decentralized AI ecosystem,” he said.

Most of Tigris’s 4,000-plus customers are similar to Fal.ai: AI startups that build image, video and audio models, and which tend to have large, latency-sensitive data sets.

“Imagine you are talking to an AI agent who is recording local audio,” Tariq said. “You want the lowest latency. You want your account to be local, close by, and you want your storage to be local, too.”

He added that large clouds are not optimized for AI workloads. Streaming large datasets for training or running real-time inference across multiple regions can create response time bottlenecks, slowing down model performance. But the ability to access local storage means that data is retrieved faster, which means developers can run AI workloads reliably and more cost-effectively using decentralized clouds.

“Tigris allows us to scale our workloads in any cloud by providing access to the same data file system from all of these places without charging egress fees,” said Fal’s Taskaya.

There are other reasons why companies want data closer to their distributed cloud options. For example, in highly regulated fields like finance and healthcare, one of the big barriers to adopting AI tools is that companies need to ensure data security.

Another driver is that companies increasingly want to own their data, Tariq says, pointing to what Salesforce did earlier this year. It blocked its competitors in the field of artificial intelligence From using Slack data. “Companies are becoming more aware of how important data is, how it feeds LLM students, and how it feeds artificial intelligence,” Tariq said. “They want to be more in control. They don’t want someone else to be in control.”

With the new funds, Tigris intends to continue building out its data storage centers to support growing demand – Tariq says the startup has grown 8x every year since its founding in November 2021. Tigris already has three data centers in Virginia, Chicago and San Jose, and wants to continue expanding in the US as well as in Europe and Asia, specifically in London and Frankfurt. And Singapore.