Blaize Appoints Industry Veteran as CRO to Drive Global Expansion

Cisco alumnus Stephen Patak joins edge AI chip designer Blaize to lead revenue and go-to-market execution as the company scales deployments worldwide.

Published on Feb. 12, 2026

Blaize, a U.S. edge AI chip designer, has appointed Cisco veteran Stephen Patak as its first Chief Revenue Officer. Patak will lead Blaize's global revenue and go-to-market strategy as the company expands deployments of its AI processor technology across public and private sector markets. The move comes after Blaize's recent SPAC merger and high-profile deal with Nokia's Singapore arm to power AI systems in the Asia-Pacific region.

Why it matters

Blaize's appointment of an experienced CRO signals the company's ambitions to rapidly scale its edge AI chip business globally, building on recent customer wins like the Nokia deal. As one of the first AI chip startups to go public, Blaize is positioning itself to be a key player in the growing market for practical, distributed AI applications across industries.

The details

Patak joins Blaize from a CRO role at cloud networking firm Nile. Prior to that, he held senior sales leadership positions at companies like Ubicquia, Here Technologies, and Extreme Networks. Crucially, Patak spent over 14 years at Cisco, including time in the Asia-Pacific region, giving him deep networking industry expertise that aligns with Blaize's focus on edge AI deployments.

  • Blaize debuted on the Nasdaq via a SPAC merger in January 2026.
  • Blaize signed a deal with Nokia's Singapore arm in 2026 to power AI systems across the Asia-Pacific region.

The players

Blaize

A U.S. edge chip designer that develops AI processor technology for distributed computing applications.

Stephen Patak

A Cisco veteran who has been appointed as the first Chief Revenue Officer of Blaize.

Dinakar Munagala

The CEO and co-founder of Blaize.

Nokia Solutions and Networks Singapore

The Singapore arm of the Finnish telecommunications company that has partnered with Blaize to power AI systems in the Asia-Pacific region.

Joseph Sulistyo

The VP of global marketing at Blaize.

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What they’re saying

“Blaize is working with cloud service providers, next-generation AI cloud operators, and infrastructure partners across both public and private sectors, to make AI part of core platforms, not just an experiment. That's a compelling stage to join, and I'm looking forward to working with the team as Blaize continues to expand.”

— Stephen Patak, Chief Revenue Officer (sdxcentral.com)

“Most of the AI compute today is happening on massive training clusters and throughput computing. So latency is not as important; you can do things offline, batch training, etc, and that's where GPUs are very good. But if you look at industries like automotive and so on, they need low latency in real time. A smart car needs to make a decision fast, for example. In our technology, the GSP is very suitable for low-latency real-time applications, like how a camera can infer a threat and take some action, or a drone, or robotics used in factory automation.”

— Dinakar Munagala, CEO and Co-founder (sdxcentral.com)

“With Nokia, we talked about a hybrid AI platform, with not only our own chip, but also a GPU like Nvidia and complementing those together as an integrated system. And we can also build an application on top of it, and we can actually also extend API services, much like a cloud service provider. They were intrigued, and said, 'You know what, why don't we try something?'”

— Joseph Sulistyo, VP of Global Marketing (sdxcentral.com)

What’s next

Blaize plans to continue expanding its partnership with Nokia beyond the initial Singapore deal, establishing the collaboration as a 'beachhead' for further growth in the Asia-Pacific region.

The takeaway

Blaize's appointment of an experienced sales leader like Stephen Patak signals the company's ambitions to rapidly scale its edge AI chip technology globally, building on recent customer wins and positioning itself as a key player in the burgeoning market for practical, distributed AI applications.