Wasabi establishes dedicated AI business led by Pinaki Mukherjee

Wasabi Technologies has announced the launch of a dedicated AI business and has named semiconductor and storage specialist Pinaki Mukherjee to lead it.

Mukherjee will serve as senior vice president and general manager of the business, which aims to bring a dedicated strategy, partnerships, and go-to-market focus as AI-driven storage demand grows.

He brings more than 20 years' experience across semiconductors, storage, and AI infrastructure, having held senior business strategy and corporate development positions at Fungible, Druva, and Western Digital. He has also previously led semiconductor strategy and AI infrastructure engagements at global consulting firm Alvarez & Marsal.

Wasabi highlighted Mukherjee's track record, which includes more than $2 billion in partnership-driven revenue and over $10 billion in strategic M&A and investment outcomes.

"Mukherjee has a track record of driving the kind of high-value partnerships that move markets, and that's exactly what this moment requires," said Wasabi president and COO Marty Falaro.

"AI workloads are pushing storage demand to a scale we've never seen, and Mukherjee is the right person to build the partnerships that extend Wasabi's position as the industry's choice for cloud storage, at the exact moment inference is reshaping what that storage needs to do."

Targeting AI infrastructure demand

Wasabi currently stores hundreds of petabytes of AI data for customers such as frontier model labs, generative AI startups, and neocloud compute providers. The firm operates 16 global storage regions and works with 18,000 channel partners globally.

The new business unit gives Wasabi a dedicated operation focused on the storage requirements of AI customers, with the vendor aiming to expand its role as demand for AI infrastructure grows.

The firm's storage framework is designed to support data across the AI lifecycle and enable customers to move data to wherever their compute resources are located without egress or API fees.

Wasabi said this approach can help organizations avoid tying their data to a single cloud provider as their AI workloads evolve, while benefiting from a more predictable cost structure.

The vendor also highlighted recent deployments, including an image- and video-generation lab that migrated 175 petabytes off a hyperscaler within months, and a robotics data consortium that has stored multiple petabytes while projecting annual savings of more than JPY 100 million.

With the new business, Mukherjee said Wasabi is well-positioned to meet the needs of its customers as they scale "beyond what any single hyperscaler ecosystem can offer."

"AI customers don't need another hyperscaler, they need the freedom to move their data wherever their workloads take them, without egress fees, API fees, or lock-in dictating their architecture," he explained. "I'm looking forward to building the ecosystem that scales that freedom across the AI ecosystem."