Hammerspace Raises 100 Million Dollars to Power AI’s Growing Data Hunger

Hammerspace has raised $100 million to expand its data orchestration platform, which enables seamless access to fragmented data across cloud and storage environments. As AI demand skyrockets, Hammerspace's Linux-based system is solving a fundamental infrastructure challenge for top tech and government clients.

Artificial intelligence might be the flashiest sector in tech right now, but beneath the surface lies a far less glamorous yet essential challenge: managing the staggering amounts of data that power AI models. That’s where Hammerspace comes in—a startup that has quietly become a crucial piece of infrastructure for some of the biggest names in tech and government. With customers like NVIDIA, Meta, Tesla, Palantir, and even the U.S. Department of Defense, Hammerspace has now raised $100 million in a strategic venture round to scale its data orchestration platform and meet surging demand.

What Hammerspace solves is deceptively simple, yet technically profound. Data in modern enterprises is scattered across multiple clouds, servers, and storage systems—often incompatible, frequently unstructured, and almost always siloed. For AI to function effectively, it needs fast, streamlined access to this data, without the lag of copying, porting, or reconfiguring. In Flynn’s words, “AI has been the perfect storm for needing what I have built.” The CEO and co-founder, David Flynn, is no stranger to innovation—he previously helped revolutionize flash computing and high-performance Linux systems. Now he’s tackling the data mess AI companies can’t afford to ignore.

Hammerspace’s solution is a high-performance data orchestration layer that unifies storage environments through a single global file system. It’s like flipping a switch that turns fragmented data into a coherent, accessible resource—one that’s always available when needed, and invisible when not. Named after the cartoon trope where characters pull objects from thin air, Hammerspace enables a similar kind of on-demand magic for data: instant access to massive datasets, wherever they live.

At the core of the platform is a file system built on Linux, more specifically on the Network File System (NFS) client—a standard element of Linux architecture that’s been rewritten and maintained by Hammerspace’s CTO and co-founder, Trond Myklebust. This low-level innovation gives the company a significant edge. Instead of layering yet another platform on top of existing infrastructure, Hammerspace plugs directly into the kernel-level operations that underpin how enterprise systems store and retrieve data. The result is speed, efficiency, and compatibility across environments that are typically hard to bridge.

The timing of this funding is no coincidence. As the AI boom accelerates, companies are realizing that without a smart, scalable data strategy, even the most sophisticated models are left underfed. “You don’t have an AI strategy without a data strategy,” said Jamin Ball, a partner at Altimeter Capital, one of the lead investors in this round. Alongside Altimeter, ARK Invest, and other unnamed strategic investors are participating, describing their involvement as “highly participatory,” suggesting deep operational interest rather than passive financial backing.

Despite minimal marketing efforts, Hammerspace has gained traction primarily through word-of-mouth among engineers and enterprise architects. With this new funding, the company plans to change that. It will scale its sales and marketing operations to reach more customers navigating the same data bottlenecks. The strategic nature of this raise and the quality of its backers hint at bigger ambitions on the horizon.

Those ambitions may include going public, though not imminently. Flynn originally floated the idea of an IPO in 2024, but now says the likely timeline is around two years out, depending on market conditions. “Yes, IPO is the Hammerspace intended strategy,” Flynn confirmed. The company is in it for the long haul, positioning itself as a key enabler of enterprise AI at scale.

The broader context here is telling. While much of the investment spotlight shines on flashy AI products and foundational models, the infrastructure layer, where data is organized, optimized, and delivered, is becoming just as critical. In this AI arms race, companies like Hammerspace are building the supply lines that ensure models stay trained, accurate, and fast. As the sector matures, data orchestration is poised to become not just a backend necessity but a front-and-center strategic advantage.