Blaize and Winmate Sign Strategic Partnership Agreement to Bring AI to Rugged Systems for Defense and Critical Infrastructure

Joint solutions combine Blaize’s energy-efficient and industrial-grade AI chips with Winmate’s rugged platforms – including drones, handhelds, vehicle-mounted units, and embedded edge devices used by defense, border security, maritime, and healthcare operators.

Blaize Holdings, Inc., and Winmate Inc., a publicly traded company in Taiwan, announced they have signed a Strategic Partnership Agreement (“Agreement”) with an intent to close approximately $15 million in business during the first year. The two companies will integrate Blaize’s AI chips into Winmate’s rugged systems, including drones, handhelds, vehicle-mounted units, and embedded devices that have to keep working in the field, often in places where regular hardware can’t survive.

The companies expect the Agreement to be the start of a much larger, multi-year relationship.

Why this partnership matters

Most AI today runs in large data centers rather than at the edge, where decisions must be made in real time. This model is often impractical for soldiers at remote posts, Coast Guard crew at sea, or medics in field clinics. They often don’t have a reliable network connection, and even when they do, they can’t afford to wait for an application to respond from halfway across the globe.

That’s the gap Blaize and Winmate intend to address through this partnership. Blaize’s chips were designed to industrial grade specifications and run AI directly on the device, with no cloud dependency. Winmate’s systems are purpose-built to perform in extreme environments, including heat, cold, dust, vibration, and rough handling. Together, they deliver real-time AI capabilities exactly where it’s needed, whether in drones, field units, the patrol vehicles, or diagnostic devices.

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A fast-growing market

Demand for on-device AI is accelerating. According to BCC Research^[1], the global edge AI market is projected to grow from $11.8 billion in 2025 to $56.8 billion by 2030, a 36.9% compound annual growth rate. Defense agencies, governments, hospitals, ports, and critical infrastructure operators all demand AI that can run securely on their equipment, without sending sensitive data over public networks.

From the leaders

“Our customers can’t wait, and they often can’t rely on the cloud. They need AI that runs where the work happens. Winmate makes some of the most capable rugged systems in the industry, and our chips are designed to run AI inside exactly those kinds of devices. This partnership turns a years-long vision into a practical, deployable answer for defense and critical infrastructure operators,” said Dinakar Munagala, CEO of Blaize, Inc.

“Our platforms are deployed on naval vessels, in border outposts, on industrial sites, and in disaster zones – environments where most hardware fails. With Blaize, we can now deliver those same systems with on-device AI built in, giving customers real-time intelligence wherever they operate,” said Ken Lu, Chairman and CEO of Winmate Inc.

Target applications

• Border security and surveillance: Real-time threat detection and perimeter monitoring
• Mobile command and control: On-site intelligence and situational awareness for field teams
• Drones and unmanned systems: Autonomous navigation and mission execution for UAVs and ground vehicles
• Critical infrastructure: Continuous monitoring and predictive analytics for power, ports, and transportation
• Maritime domain awareness: Vessel tracking and anomaly detection at sea
• Field healthcare: Portable diagnostics and decision support in remote and disaster environments

Deal at a glance

• First-year revenue: the parties intend to work in good faith to close approximately $15 million in business, expected to scale meaningfully in subsequent years
• Term: Three-year initial term, with automatic renewal
• Next steps: Joint engineering, sales, and marketing execution to bring integrated systems to market, with additional opportunities to be added through follow-on programs