Bright Machines Scores $126 Million Series C

<p><strong><span class&equals;"legendSpanClass"><span class&equals;"xn-location">SAN FRANCISCO<&sol;span><&sol;span><&sol;strong> &&num;8212&semi; <u>Bright Machines<&sol;u>&comma; an innovator in intelligent&comma; software-defined manufacturing and robotics&comma; has raised <span class&equals;"xn-money">&dollar;126 million<&sol;span> in Series C funding&comma; with <span class&equals;"xn-money">&dollar;106 million<&sol;span> in equity led by investment from funds and accounts managed by BlackRock and participation from NVIDIA&comma; Microsoft&comma; Eclipse&comma; Jabil and Shinhan Securities&comma; and with <span class&equals;"xn-money">&dollar;20 million<&sol;span> in venture debt from J&period;P&period; Morgan&period; This brings the company&&num;8217&semi;s total amount raised to more than <span class&equals;"xn-money">&dollar;400 million<&sol;span>&period; The capital will be used to launch product innovations&comma; expand its software stack for increased assembly flexibility&comma; and grow strategic relationships with ecosystem partners&period;<&sol;p>&NewLine;<p>Currently&comma; electronics manufacturing is outdated and manual with isolated&comma; inefficient processes that drive up costs&period; With the proliferation of AI driving up demand for compute power and subsequently&comma; AI hardware&comma; the industry faces a bottleneck across dozens of fragmented vendors that causes a supply chain traffic jam&period; Bright Machines was founded in 2018 by industry veterans who saw a unique opportunity to solve this problem and bring an unprecedented&comma; data-focused approach to electronics manufacturing&period;<&sol;p>&NewLine;<p>Bright Machines&&num;8217&semi; full stack solution provides centralized data visibility&comma; traceability&comma; performance benchmarking&comma; and flexible automation&period; In Bright Machines&&num;8217&semi; digital ecosystem&comma; valuable data is constantly generated and communicated to a central hub&comma; thus creating a powerful engine for continual optimization&period; Leveraging this robust data network&comma; Bright Machines&&num;8217&semi; Design for Automated Assembly &lpar;DFAA&rpar; tool provides virtual design recommendations to shorten products&&num;8217&semi; time to market&period; The company&&num;8217&semi;s robotics utilize machine learning algorithms to help ensure quality control and traceability during assembly inspection&period; And once products reach their end of life&comma; Bright Machines&&num;8217&semi; flexible disassembly capabilities help harvest and recycle components – achieving full circular manufacturing&period; By uniting this data network with agile robotics&comma; modeling and simulation&comma; Bright Machines provides a robust&comma; modern factory that far exceeds what traditional factories can achieve&period;<&sol;p>&NewLine;<p>&&num;8220&semi;Adopting ecosystem-wide&comma; software-defined manufacturing processes will ease the mounting burden from the industry&&num;8217&semi;s biggest challenges&comma; including a lack of skilled workforce&semi; aging&comma; rigid systems&semi; disparate and fragmented supply chains&semi; and an overall lack of standards across the value chain&comma;&&num;8221&semi; said <span class&equals;"xn-person">Lior Susan<&sol;span>&comma; CEO and Executive Chairman at Bright Machines&period; &&num;8220&semi;By collaborating with technology leaders such as NVIDIA and Microsoft&comma; Bright Machines can deliver flexible&comma; integrated&comma; and intelligent manufacturing solutions to our customers&comma; starting with Design for Automated Assembly &lpar;DFAA&rpar; and continuing – with unprecedented visibility – through every step of the process&comma; right through to the circularity of recycling&period; As optimized manufacturing systems are faster&comma; more resilient&comma; and more efficient than their manual counterparts&comma; our customers are more competitive in terms of cost&comma; their products&&num;8217&semi; time-to-market&comma; and customer delight&period; And in a world where we can now use AI and software to teach robotics systems how to build electronics&comma; the opportunity to redefine how we will design and build electronics is unlimited&period;&&num;8221&semi;<&sol;p>&NewLine;<p>&&num;8220&semi;Physical AI is powering the next wave of digitalization applications&period; Bright Machines&comma; powered by NVIDIA Omniverse core technologies&comma; will help accelerate a new era of AI-enabled industrial digital twins — from design to operation and optimization&comma;&&num;8221&semi; said Rev Lebaredian&comma; VP of Omniverse and Simulation Technology&comma; NVIDIA<&sol;p>&NewLine;

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