""Modern AI workloads and AI infrastructure are choosing distributed computing instead of big cloud," Ovais 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 localized data storage centers that it claims can meet the distributed compute needs of modern AI workloads."
"The startup's AI-native storage platform "moves with your compute, [allows] data [to] automatically replicate to where GPUs are, supports billions of small files, and provides low-latency access for training, inference, and agentic workloads," Tariq said. To do all of that, Tigris recently raised a $25 million Series A round that was led by Spark Capital and saw participation from existing investors, which include Andreessen Horowitz, TechCrunch has exclusively learned."
Demand for AI compute has driven growth of specialized providers like CoreWeave, Together AI and Lambda Labs offering distributed GPU capacity. Most companies still store data with AWS, Google Cloud and Microsoft Azure, whose storage prioritizes proximity to their own compute and not multi-cloud distribution. Modern AI workloads are shifting toward distributed compute, creating a need for storage that replicates data to where GPUs are and provides low-latency access. Tigris, founded by the team behind Uber's storage platform, is building localized data centers and an AI-native storage layer to meet those needs and secured a $25 million Series A led by Spark Capital with Andreessen Horowitz participating.
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