Company Overview
About Bright Machines
Bright Machines is a San Francisco, California-based intelligent manufacturing automation company — backed with $400+ million in total funding including a $126 million Series C in June 2024 led by BlackRock with NVIDIA, Microsoft, Eclipse Ventures, and Jabil — providing discrete manufacturers in electronics, industrial, and consumer goods sectors with a full-stack automation solution combining Microfactory robotic cells (reconfigurable hardware for assembly, inspection, and testing) with the Brightware intelligent software platform that uses AI and computer vision to enable flexible, self-adapting automation lines that can be reconfigured between products within hours rather than weeks. Founded in 2018 by co-CEO Amar Hanspal (former co-CEO and Chief Product Officer at Autodesk, the $36 billion design software company) and other founding team members with Autodesk and manufacturing automation backgrounds.
Business Model & Competitive Advantage
Bright Machines' Microfactory approach addresses the flexibility gap in traditional factory automation: conventional robotic assembly lines (built with proprietary robots from Fanuc, ABB, or KUKA, custom tooling, and rigid programming) require 6-18 months to commission and $2-10 million in capital per line — creating automation that is cost-effective only for decade-long high-volume, single-product runs. When product generations change (a new phone model, a new PCB design), the tooling and programming changes require weeks of downtime and additional engineering investment. Bright Machines' software-defined automation (Brightware programming the same physical cells for different products through AI-guided vision and motion planning, with reconfiguration through software changes rather than hardware rebuilds) provides the flexibility that consumer electronics and industrial equipment manufacturers need to automate SKU-diverse, generation-changing production without the traditional fixed automation cost and inflexibility penalty.
Competitive Landscape 2025–2026
In 2025, Bright Machines competes in the intelligent manufacturing automation, software-defined manufacturing, and AI robotics market with Covariant (AI robotic picking, $222M raised), Machina Labs (AI sheet metal forming, $35M raised), and Veo Robotics (human-robot collaboration, $35M raised) for electronics and industrial manufacturer intelligent assembly and inspection automation platform adoption. BlackRock's Series C leadership reflects institutional conviction in AI manufacturing infrastructure. NVIDIA's and Microsoft's participation align Bright Machines with the dominant AI computing and enterprise software ecosystems for manufacturing AI development. Jabil's participation (global electronics manufacturing services, $29B revenue) provides contract manufacturing customer channel access. The 2025 strategy focuses on growing AI hardware infrastructure manufacturing (building automation lines for NVIDIA GPU server assembly, semiconductor packaging, and battery cell production), expanding Brightware software licensing to third-party robot hardware platforms, and building the autonomous quality inspection workflow for high-precision electronics manufacturing.
The Bright Machines Story
Founders
Company Timeline
Major milestones in Bright Machines's journey
Leadership Team
Meet the leaders behind Bright Machines
Lior Susan
Lior Susan serves as CEO of Bright Machines. He is also the founder and managing partner of Eclipse Ventures, which incubated and invested in Bright Machines. He took over as interim CEO in December 2021.
Amar Hanspal
Amar Hanspal co-founded Bright Machines in 2018 and served as CEO until December 2021. He previously served as co-CEO and Chief Product Officer at Autodesk, where he led the company's transition to SaaS.
Open Positions
Reddit Discussions
Key Differentiators
Emerging Innovator
Bright Machines is an emerging player bringing innovative solutions to the Robotics market.
Growth Stage
Bright Machines has achieved $400M in revenue, demonstrating strong product-market fit.
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