Bright Machines is funding software-defined manufacturing for AI infrastructure

Bright Machines raised $126 million in Series C funding in June 2024 to expand software-defined manufacturing for electronics and AI infrastructure assembly.

Published: 2024-06-25

Type: FUNDING

Tags: Ai Infrastructure, Series C, Software Defined Manufacturing

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Bright Machines is funding software-defined manufacturing for AI infrastructure

Bright Machines raised $126 million in Series C funding in June 2024 to expand software-defined manufacturing for electronics and AI infrastructure assembly.

Bright Machines raised $126 million in Series C funding on June 25, 2024, with $106 million in equity and $20 million in venture debt. The company said total capital raised exceeded $400 million, putting late-stage funding behind software-defined manufacturing for electronics and AI infrastructure.

The event fits a long manufacturing-software arc. Bright Machines says it was founded in 2018 to transform manufacturing and later deployed microfactories, Brightware software, and automated assembly capabilities. The Series C funded software expansion and strategic relationships as AI hardware demand increased.

Bright Machines sells a factory operating layer around robotics, software, and data traceability. Its Bright Factory model builds data-center infrastructure for hyperscalers. AI infrastructure customers care about repeatability, fast design iteration, and supply-chain resilience.

Bright Designer extends the factory story upstream. In March 2025, Bright Machines previewed a web application for design engineers to make CPU- and GPU-based server designs easier to automate before manufacturing begins. The product shifts automation from factory-floor retrofits toward design-for-automated-assembly decisions.

TechCrunch background coverage traced Bright Machines back to software-defined microfactories and a large 2018 Series A. Bright Machines is now trying to turn that software-defined factory thesis into named AI-infrastructure programs where production volume, yield improvement, and assembly-line economics can be evaluated.

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