Mechanical Engineer

Bright Machines says its new hybrid robot cell could help solve a major AI infrastructure bottleneck. Bright Machines announced the Hybrid BRC to solve quality data disruption during manual assembly in AI server production, addressing key yield and speed bottlenecks for hyperscalers. Bright Machines wants to solve one of the least glamorous but most consequential problems in the AI buildout: what happens to quality data when a human being has to touch the production line. The San Francisco-based manufacturer announced today the Hybrid BRC (Bright Robotic Cell), an expansion of its Bright Factory platform that lets human operators step inside a sensor-monitored robotic cell to perform prescribed assembly steps - without breaking the digital record that tracks every server from its first screw to its shipping label. It sounds like an incremental hardware update. It isn't. The Hybrid BRC is a direct answer to a structural weakness in high-stakes electronics manufacturing - one that CEO Sviat Dulianinov quantified in stark terms in an exclusive interview with VentureBeat. "If you assemble modern AI servers starting with manual operations, your initial yield - first-pass yield - can be as low as 20%," Dulianinov said. "Then you gradually ramp up and scale, and it can reach the 60s, 65% or so." When a single AI server can cost hundreds of thousands of dollars, and hyperscalers are burning billions waiting for infrastructure they can't deploy fast enough, that number is the whole story. The Hybrid BRC is Bright Machines' attempt to keep human hands in the loop without letting human error back in the door. Why manual assembly steps create a black hole in production data Dictionaries & Encyclopedias Modern automated assembly lines generate a continuous stream of production data - torque values, placement coordinates, component serial numbers, inspection images. That "data thread" is what lets a manufacturer prove a server was built correctly and, when something fails in the field months later, trace the failure back to a specific station, step, or part. But automated lines inevitably need manual intervention, and until now manufacturers had two bad options when that happened: stop the line entirely, or pull in-process units off to a separate manual workstation that sits outside the monitored data flow. The first choice kills throughput. The second punches a hole in the production record at precisely the moment when human error is most likely to occur. The Hybrid BRC eliminates that tradeoff, the company says. The cell incorporates guarded access doors and safety panels directly into the production line. When an operator opens the doors, the robotic arm deactivates, and on-screen instructions guide the operator through each assembly step while the cell's sensor array - cameras, force feedback, and tooling sensors - continues monitoring for incorrect installs, missed steps, and wrong components, applying the same quality checks used during full automation. The traceability record persists at the serial-number level from start to finish. The yield gap between humans and robots in AI server assembly The economics driving the design become clear when Dulianinov's manual-assembly figures are set against what automation delivers. "At robotic operations, yield-per-station level is usually more than 98% with our technology, and even at the line level, we usually get to 97.5%, 97.7% or so," he said. First-pass yield measures the percentage of units that come off the line correct the first time, without rework. The gap between a 20% manual ramp and a 98% automated station isn't a rounding error - it's the difference between profitability and disaster on hardware this expensive. That math explains the company's design philosophy for the Hybrid BRC, which treats the human operator as an escape valve for exceptions rather than a substitute for automation. "The more human stations you introduce, the more you increase the risk of lower yields driving the overall yield down," Dulianinov said. "That's why we prefer to start at least with 50% automation, and then move to at least 80%." Speed follows a similar pattern: "On the line level, robots can be faster than humans from like 50 to 100%" in throughput terms, he said. How server assembly became the hidden bottleneck of the AI infrastructure race The AI infrastructure conversation usually revolves around chip supply, power availability, and data center construction. Dulianinov argues that assembly - the unglamorous work of turning chips and motherboards into racked, tested, deployable compute - is a quietly enormous drag on deployment timelines. "When you have the chips and you have the motherboards, you want to be as fast as possible to deploy that in the data center," he said, describing greenfield deployments where power and buildings already exist. Getting hardware built, tested, and often rebuilt when quality falls short "could be months," he said. "With more technology used for this, as our tech, we believe that we can cut it by at least a third." Dictionaries & Encyclopedias A company executive on the call added an anecdotal but telling data point: the servers Bright Machines produces are "flying out into production" rather than sitting stacked in warehouses awaiting deployment - evidence that assembly capacity, not just chips or power, gates hyperscaler timelines. The stakes are asymmetric, the executive noted, because the largest hyperscalers lose millions of dollars per day when servers fail or arrive late. That is why customers are less interested in buying boxes than in buying assurance - and why an unbroken data thread has become a product in its own right. Inside the secretive customer base already running hybrid production lines The Hybrid BRC is not vaporware. Dulianinov said the company already operates a number of the hybrid lines in the U.S. and has "built more than 10,000 compute nodes" through the new stations. This year, he said, Bright Machines plans to manufacture "more than half a gigawatt of compute capacity." Who's buying? Don't ask. "We cannot unfortunately name customers. That's the toughest part of our job," Dulianinov said. "They're pretty secretive because, as you can imagine, everything data center related is IP related." He did offer growth figures: customers grew "more than 3x this year" versus the prior year, driven by what he called the intersection of "physical AI, AI infrastructure buildout, and onshoring." The demand is spilling into real estate - the company is moving from its 16th Street San Francisco offices to a Burlingame space this fall that executives described as three to four times larger. Overall, the company says it has deployed more than 130 microfactories across 10-plus countries, served more than 60 customers, and produced more than 300,000 servers. What separates Bright Machines from Tulip, Instrumental, and contract manufacturing giants Asked how the Hybrid BRC's traceability claims stack up against operator-guidance and inspection software vendors like Tulip and Instrumental, Dulianinov drew a sharp line around business models. "Tulip is just a company that does interface for operators. Instrumental, they focus on inspection. It's just pieces of the puzzle," he said. "We, as a technology-enabled manufacturer, we actually run this whole operation... We put our lines, put our software, put our data on the floor, our people, and run it from the beginning to the end." The right comparison set, he argued, is contract manufacturing giants like Flex, Jabil, and Foxconn - companies that own the full production process but historically built it on manual labor that generates little data. Bright Machines' differentiation, he said, is that robot data, sensor data, and now human-station data all flow through one orchestration layer into a single environment the company calls Bright Insights. That positioning is notable given the company's origins. Bright Machines was carved out of contract manufacturer Flex eight years ago, and its history has had turbulence: the company planned to go public in 2021 via a SPAC merger at a reported $1.6 billion valuation, according to contemporaneous reporting by The Wall Street Journal and CFO Dive, before the deal fell through. Ad slot ready: 5887729102 Discover more Businesses Psychology Dictionaries & Encyclopedias

Bright Machines expands Bright Factory platform with Hybrid BRC for resilient AI infrastructure production. Context-aware monitoring and full production traceability now extend to human touchpoints on the line, without compromising speed or safety Bright Machines, a next-generation manufacturer bringing AI and data center infrastructure production to the edge, announced today the Hybrid BRC (Bright Robotic Cell), an enhancement to its Bright Factory platform. This allows human operators to perform prescribed assembly steps inside a sensor-monitored robotic cell when manual assistance is required, preserving the production record from start to finish. For manufacturing high-value AI infrastructure, this is the only solution delivering this level of traceability when flexibility is essential for maintaining operational performance. More headlines. Articles. The manufacturing space has had two imperfect options when an automated line needs manual intervention: stop the line or move the in-process units to a separate manual station that is not connected to the same production data thread. That data thread gap made it harder to verify proper procedure was followed, pinpoint the source of a quality issue, or analyze failures in the field. By implementing the Hybrid BRC and bringing operator-assisted work inside its monitored production flow, Bright Machines can address this data gap challenge head on. "AI infrastructure customers need a manufacturing partner that can keep pace when manual intervention is required without trading away data insights," said Sviat Dulianinov, CEO of Bright Machines. "The Hybrid BRC lets us do exactly that, keeping the full production record intact while preserving traceability throughout the production process. That combination strengthens our commitment to delivering high quality and flexible operations for our customers with no tradeoff on scale or security." Built using experience learned from Bright Machines' BRC, a modular, software-defined cell that redefined assembly automation, the Hybrid BRC expands that foundation with added flexibility. It incorporates guarded access doors and safety panels as a core part of the production line, enabling the safe inclusion of human operators whenever required. When the doors are opened, the robotic arm at the station is deactivated, allowing the operator to enter the cell and maintain production continuity with on-screen assembly instructions guiding every step. The Hybrid BRC then monitors for incorrect installs, missed steps, and wrong components, applying the critical quality checks as when the line is running at full automation. This preserves the Bright Machines traceability record at the serial-number level from start to finish. If an issue surfaces later in the field, the complete dataset is readily available for analysis within the Bright Factory platform. "The future of manufacturing isn't choosing between automation and flexibility - it's combining both in the same digital production environment," said Lior Susan, Founder and CEO of Eclipse, and Chairman and Co-Founder of Bright Machines. "The Hybrid BRC solves one of the industry's toughest challenges: preserving traceability and data integrity even when human intervention is required." Now available as part of the Bright Factory platform, the Hybrid BRC helps maintain production continuity while preserving traceability when manual intervention is required. For customers seeking a resilient and trustworthy path from silicon to revenue, reach out to [email protected] or visit brightmachines.com for more information. About Bright Machines Bright Machines is a next-generation manufacturer bringing AI and data center infrastructure production to the edge. By embedding software-defined automation, AI-driven quality enforcement, and unified manufacturing data directly into customer and partner facilities, Bright Machines delivers fast, consistent, and adaptable production of highly complex systems, maintaining traceability and control as products and configurations evolve. With experience from deploying more than 130 microfactories across 10+ countries and 60+ customers, Bright Machines brings deep manufacturing excellence to one of the most demanding production environments in the world. Backed by BlackRock, NVIDIA, Microsoft, and Eclipse, Bright Machines is headquartered in San Francisco, California. For more information, visit brightmachines.com.

Introducing Chris Stori, Verkada's new Chief Information Officer. Mar 31, 2026 Filip Kaliszan Chief Executive Officer As Verkada continues to grow into the defining platform for the physical world, building the right internal foundation is just as critical as the technology Verkada deliver to customers. That's why I'm pleased to welcome Chris Stori as its new Chief Information Officer. Chris will lead its corporate IT strategy, business systems, and the broader technology infrastructure that powers Verkada's operations as Verkada scale globally. His work will be central to ensuring that every team at Verkada has the tools and systems they need to operate at scale and serve its customers well. "Verkada is redefining what's possible with Physical AI and delivering real-world impact. I am excited to join the team and focus on scaling our global business operations and internal infrastructure to further deepen our impact across industries and markets." - Chris Stori, Chief Information Officer at Verkada Chris comes to Verkada most recently from Bright Machines, where he served as CEO. Before that, he spent 11 years at Cisco in a series of high-impact leadership roles, including Senior Vice President and General Manager of Networking Experiences. In that role, he oversaw the multi-billion-dollar Enterprise Networking, IOT, and Meraki portfolio, and was a key driver in scaling Meraki from 18,000 to over 600,000 customers. That kind of growth doesn't happen by accident; it takes operational rigor, a relentless focus on user experience, and the ability to build systems that scale. Chris has done it before, and he'll bring that same mindset to Verkada. Chris joins at an exciting moment. Verkada recently announced the availability of AI-powered deterrence, a proactive security solution that uses large vision, audio, and language models to autonomously detect and warn potential intruders before a crime occurs. As Verkada continue to invest in agentic security intelligence and expand its global footprint, having the right internal infrastructure is essential to building safer, smarter communities. Chris is exactly the leader to build it. Interested in joining the team? Check out open roles on its careers page.