As the adoption of AI drives up demand for computing power, the company is working to help meet exploding demand for AI hardware.
SAN FRANCISCO—Software and robotics company Bright Machines offers a full stack of automation tools for building what it calls “the AI backbone”—artificial intelligence (AI) hardware. By integrating computer vision, machine learning, and software applications, the company aims to transform the way products can be designed and manufactured.
Bright Machines recently raised $126 million in Series C funding that will be directed to help meet “skyrocketing demand as pressure builds to support AI hardware production,” the company said in a release. Bright Machines said it plans to use the newly raised capital to launch product innovations, expand its software stack for increased assembly flexibility, and grow strategic relationships with ecosystem partners.
The Series C funding includes $106 million in equity led by investment from funds and accounts managed by BlackRock, with participation from NVIDIA, Microsoft, Eclipse, Jabil and Shinhan Securities. It also includes $20 million in venture debt from J.P. Morgan, the company said.
“There is a global need for manufacturing transformation if we are going to reap the benefits of AI innovation,” said Shinhan Securities Global Equity Team Executive Director Damian Kang, in the release. “Bright Machines delivers reliable access to more AI hardware and transforms its manufacturing, ensuring the ecosystem can take advantage of all that AI has to offer.”
In the release, Bright Machines characterized electronics manufacturing as “outdated and manual, with isolated, inefficient processes that drive up costs.” As the proliferation of AI drives up demand for compute power and, subsequently, AI hardware, the industry faces a bottleneck across dozens of fragmented vendors, resulting in a supply chain traffic jam.
To solve this problem, Bright Machines was founded in 2018 by industry veterans who saw an opportunity to bring what they viewed as “an unprecedented, data-focused approach to electronics manufacturing.”
Bright Machines said in the release that its full stack offering provides centralized data visibility, traceability, performance benchmarking, and flexible automation. In the company’s digital ecosystem, valuable data is constantly generated and communicated to a central hub, creating a powerful engine for continual optimization.
Bright Machines’ Design for Automated Assembly (DFAA) tool uses this data network to provide virtual design recommendations that are reported to shorten a product’s time to market. The company’s robotics use machine learning algorithms to help ensure quality control and traceability during assembly inspection. Once products reach their end of life, Bright Machines’ flexible disassembly capabilities help harvest and recycle components to achieve full circular manufacturing.
By uniting this data network with agile robotics, modeling, and simulation, Bright Machines said it provides “a robust, modern factory that far exceeds what traditional factories can achieve.”
“Adopting ecosystem-wide, software-defined manufacturing processes will ease the mounting burden from the industry’s biggest challenges, including a lack of skilled workforce; aging, rigid systems; disparate and fragmented supply chains; and an overall lack of standards across the value chain,” said Bright Machines CEO and Executive Chairman Lior Susan, in the release. “By collaborating with technology leaders such as NVIDIA and Microsoft, Bright Machines can deliver flexible, integrated, and intelligent manufacturing solutions to our customers, starting with Design for Automated Assembly (DFAA) and continuing—with unprecedented visibility—through every step of the process, right through to the circularity of recycling.
“As optimized manufacturing systems are faster, more resilient, and more efficient than their manual counterparts, our customers are more competitive in terms of cost, their products’ time-to-market, and customer delight,” he continued. “And in a world where we can now use AI and software to teach robotics systems how to build electronics, the opportunity to redefine how we will design and build electronics is unlimited.”
In addition to supporting Bright Machines’ vision, the funding round also highlights the intense pressure that large cloud compute providers are facing to scale AI infrastructure across compute, data storage, and related network capabilities to meet increasing demand, the company said.
“There is a fundamental shift in the way electronics manufacturing must adapt to enable the rapid progress and adoption of AI,” said Marc Stoll, partner at Eclipse, in the release. “Bright Machines’ full-stack solution changes the status quo by providing flexible automation across all stages of the manufacturing life cycle from product design to assembly to disassembly. The team at Bright Machines sees the power of combining robotics and AI in the physical world and is uniquely positioned to transform the manufacturing lifecycle through automation.”
The news of the investment came on the heels of Bright Machines’ recent integration and go-to-market partnership with Microsoft Azure, a partnership that aims to enable an accessible, efficient, and data-driven manufacturing process for electronics manufacturers.
“Physical AI is powering the next wave of digitalization applications,” said Rev Lebaredian, vice president of Omniverse and Simulation Technology, NVIDIA, in the release. “Bright Machines, powered by NVIDIA Omniverse core technologies, will help accelerate a new era of AI-enabled industrial digital twins—from design to operation and optimization.”