A fresh wave of capital is flowing into the cloud storage layer that quietly underpins everything from generative AI experiments to global media pipelines, and this time the spotlight lands squarely on Wasabi Technologies. The Boston-based company has announced a $70 million equity funding round led by L2 Point Management, with strategic participation from Pure Storage and continued backing from existing investors including Fidelity Management & Research Company. The round pegs Wasabi’s valuation at $1.8 billion and lifts total funding to more than $600 million, a signal that investors see storage not as plumbing, but as a decisive competitive lever in the AI era. The capital is earmarked for accelerating Wasabi’s push into AI infrastructure, expanding its global footprint, and rounding out a product portfolio designed for enterprises and AI developers drowning—sometimes quietly—in data.
What makes this moment interesting is how deliberately Wasabi positions itself against the hyperscalers. Since launching Hot Cloud Storage in 2017, the company has hammered on a single, slightly contrarian idea: predictable pricing matters as much as raw performance. No egress fees, no API request charges, no surprise line items quietly inflating AI experiments into budget nightmares. That philosophy now extends deeper into AI-centric offerings like Wasabi AiR, where AI-powered metadata tagging turns vast object stores into something actually navigable, and Wasabi Fire, an NVMe-based storage class aimed squarely at compute-intensive AI and machine-learning workloads—training runs, real-time inference, logging streams, media pipelines, the whole demanding mix. It’s storage that assumes data will be touched, moved, and re-used constantly, not frozen in some archival limbo.
Security, too, is treated as part of the core architecture rather than a bolt-on. Features like multi-user authorization and Covert Copy—a patent-pending, ransomware-resistant approach that keeps critical data invisible and untouchable even during an attack—reflect the reality that AI datasets are now crown jewels. Lose them, corrupt them, or expose them, and the damage ripples far beyond IT. In a slightly ironic twist, as GPUs dominate headlines and budgets, Wasabi’s pitch leans into the less glamorous truth: without resilient, high-performance, and affordable storage, AI ambitions stall fast. Kerstin Dittmar of L2 Point put it bluntly, noting that AI tools simply grind to a halt without the storage layer keeping up, no matter how advanced the compute looks on paper.
The participation of Pure Storage adds another layer of meaning to the deal. It’s not just financial; it reinforces an alliance between two companies that share a bias toward simplicity and performance over lock-in and opacity. As AI reshapes how enterprises manage data—more real-time, more iterative, more cost-sensitive—this partnership hints at a broader ecosystem play, where cloud object storage and high-performance enterprise systems converge rather than compete. Krishna Gidwani of Pure Storage framed it as building AI infrastructure that is “intelligent by design and simple to deploy,” a phrase that sounds almost modest until you remember how rarely those two qualities coexist in enterprise tech.
All of this momentum is grounded in scale that’s already very real. Wasabi now manages more than three exabytes of data across 16 global regions, serving customers that range from media giants like iHeartMedia to sports institutions such as the Boston Red Sox and Liverpool Football Club, alongside global enterprises, universities, and AI-driven businesses with heavy data-retrieval needs. It’s an eclectic mix, but that’s kind of the point: when storage pricing is predictable and performance is consistent, wildly different workloads can coexist. The funding doesn’t just buy Wasabi more runway; it buys time to entrench an idea that’s suddenly fashionable again—that boring, well-designed infrastructure, priced sanely, can be just as disruptive as the flashiest AI model.
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