Bright Machines, the San Francisco company building a software-defined manufacturing platform for AI and data center hardware, has landed a strategic investment from Teradyne, the North Reading, Mass.-based automated test equipment and robotics supplier.

Announced on October 5, 2026, the investment arrives alongside a collaboration to combine Teradyne's robotics and test technologies with Bright Machines' factory software to advance AI infrastructure manufacturing.

Deal Puts Teradyne Money Behind Software-Defined Factories

The pairing brings together two sides of the production equation. Teradyne, which trades on NASDAQ under TER, supplies robotics and test technologies to manufacturers across the AI ecosystem, including EMS and ODM providers, OEMs, and hyperscalers.

Bright Machines operates a platform covering design, robotics, automation, inspection, material movement, production intelligence, and operations, with more than 130 microfactory deployments across more than 10 countries and active AI infrastructure production in the United States.

Inside the Technical Agenda

Under the collaboration, the companies plan to evaluate integrating Teradyne technologies into Bright Machines manufacturing environments. The work spans precision robotic assembly, robotic loading and unloading of test equipment, and autonomous movement of materials across the factory.

The target deployment model is at Bright Machines' own sites and those of its customers, where the Bright Machines platform, Universal Robots collaborative robots, and Teradyne board test systems would run side by side on the production floor.

Each generates its own data stream: assembly and inspection data, robot and material-movement data, and electrical test results.

Tying those streams together with Bright Machines' product genealogy and manufacturing intelligence capabilities would give customers an end-to-end production data thread connecting design decisions, assembly execution, and electrical performance.

"What limits automation today is not what a robot can physically do but how much engineering it takes to tell it what to do," said James Davidson, chief AI officer at Teradyne.

"When a robot can pick up a new task in hours instead of being re-engineered over weeks, high-mix, short lifecycle production becomes the default.

Once build data and test data sit in the same loop, the line can correct itself quickly."

Executives Frame the Stakes

Shantnu Sharma, chief development officer at Teradyne, said physical AI is changing what is possible on the factory floor.

"The combination of Bright Machines depth in software-defined manufacturing, and Teradyne's decades of experience in robotics and testing gives companies building AI infrastructure a faster path from design into production, with data behind every unit they build," he said.

At Bright Machines, chief executive officer Sviat Dulianinov called the investment a validation of the company's approach.

"The next generation of AI infrastructure calls for a manufacturing approach that is more automated, software-defined, data-driven, and responsive to change," he said.

"Teradyne's expertise, and the investment that comes with it, helps us validate that approach. Their robotics and test technologies are complementary to our platform, and together we can help customers simplify integration, accelerate deployment, and maintain a complete production data thread."

Lior Susan, founder and CEO of Eclipse and co-founder and chairman of Bright Machines, put the case more bluntly.

"Manufacturing is where AI becomes physical," he said.

"The AI buildout will be won by companies that can turn increasingly complex hardware into production quickly, reliably, and at scale. Teradyne brings decades of leadership in robotics and testing, making them a powerful partner as Bright Machines builds the manufacturing infrastructure for the AI era."

Why AI Hardware Production Is Hard

The companies describe the manufacturing environment for AI infrastructure as unusually demanding.

Product complexity runs high, design cycles are short, quality requirements are stringent, and schedules leave little room for rework.

Manufacturing has become a determinant of deployment speed, quality, and economic value as hyperscalers, AI laboratories, silicon providers, and OEMs pour investment into next-generation compute, and manufacturers increasingly prize lines that can be reconfigured in software as product designs refresh.

Against that backdrop, both companies argue for an integrated approach: manufacturing design, intelligent robotics, autonomous material movement and inspection, and end-to-end production intelligence delivered as one coordinated system.

The combination of Bright Machines' software-defined platform and Teradyne's robotics and test portfolio is intended to bring those pieces together for AI infrastructure buildouts, which the companies describe as one of the largest electronics manufacturing buildouts in recent history.

Who the Companies Are

Bright Machines positions itself as a next-generation manufacturer bringing AI and data center infrastructure production to the edge.

The company embeds software-defined automation, AI-driven quality enforcement, and unified manufacturing data into customer and partner facilities, aiming for fast, consistent, and adaptable production of highly complex systems with traceability maintained as products and configurations evolve.

Beyond its microfactory track record across more than 10 countries, Bright Machines serves more than 60 customers and is backed by BlackRock, NVIDIA, Microsoft, and Eclipse.

Teradyne designs, develops, and manufactures automated test equipment and advanced robotics systems, with semiconductor and electronics test solutions spanning its market.

The company is headquartered in North Reading, Massachusetts.