Why Wasabi Thinks Storage Is the Real AI Bottleneck

Wasabi Technologies has raised $70 million in new funding, bringing its valuation to about $1.8 billion. The funding is fuel to keep building storage that works well for AI, is easier to secure, and doesn’t come with surprise costs.

Wasabi touts funding as sign of strength and opportunity

The round was led by L2 Point Management, with Pure Storage and longtime investor Fidelity Management & Research Company also participating. All in, Wasabi has now raised more than $600 million since it launched in 2017.

Basically, the money gives Wasabi room to keep building out storage optimized for AI, expand into more regions, and keep up with how fast data volumes are growing as more companies start using AI in real-world work.

“We’re ushering in the next generation of cloud storage, powering data-intensive workloads like generative AI and autonomous systems,” said David Friend, co-founder and CEO of Wasabi Technologies, in the announcement. 

“This funding underscores Wasabi’s strong market position and continued growth as enterprises and AI developers alike seek a better, more predictable alternative to the hyperscalers.”

Storage in the (AI) spotlight

A lot of the AI hype right now is about chips and raw computing power, but storage is the quiet piece that can slow everything down. AI needs vast amounts of data, and that data has to be easy to access, move around, and keep secure. If storage is slow or too expensive, it doesn’t matter how powerful the rest of the system is. Everything bottlenecks there.

“Storage may not receive the same attention as GPUs, but without it, the use of AI tools and technology grinds to a halt,” said Kerstin Dittmar, managing partner and chief investment officer of L2 Point. “Wasabi’s innovative solutions help to make storage both high-performance and affordable, and we look forward to supporting the company’s next stage of growth.”

Wasabi’s appeal has historically been its flat-rate “hot cloud storage” model. 

You pay a flat rate for storage, with no extra charges for moving or accessing your data. 

That’s been a big deal for customers who are tired of cloud bills creeping up in unpredictable ways, especially as the amount of data they’re storing keeps growing fast.

Building out an AI-ready storage stack

Over the past couple of years, Wasabi has grown past being “just storage.” They added something called Wasabi AiR, which basically helps automatically organize data so it’s easier to find and use later, rather than getting lost once it’s uploaded. 

More recently, they launched Wasabi Fire, a much faster storage option created for teams doing heavier AI and machine learning work (think training models, running them in real time, and handling a ton of data all at once).

Security has moved up the priority list as well. Wasabi added Covert Copy, a ransomware-resistant capability that creates hidden, locked-down backups that can’t be messed with or deleted without multiple approvals. 

The goal is to protect critical data as attackers increasingly target backup systems directly.

Pure Storage’s investment in particular highlights the overlap between traditional storage players and cloud-native platforms. 

“AI is changing the way enterprises manage and store data,” said Krishna Gidwani, vice president of strategy and corporate development at Pure Storage. “Our investment reflects a shared focus on building the next generation of AI infrastructure that is intelligent by design and simple to deploy and operate.”

Today, Wasabi manages more than three exabytes of data across 16 global regions and serves customers spanning media, backup, enterprise IT, and analytics. 

AI is only going to keep pushing data growth higher, so the company is being smart by positioning storage not as background infrastructure, but as a core part of the AI stack itself.

That same shift is happening across the channel, where infrastructure teams and partners are talking about how to modernize stacks for AI and rethink traditional architectures so they actually keep up with today’s workloads. You can check out one recent look at those trends here.