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Rivian spinout Mind Robotics valued at $2 billion in Series A funding round

ReutersMar 11, 2026 6:04 PM
  • Accel's Sameer Gandhi joins Mind Robotics' board
  • Mind Robotics, a Rivian spin-out, operates with the EV maker as partner
  • Experts warn commercializing advanced robotics requires vast data for model training

By Akash Sriram

- Mind Robotics, a startup spun out of EV maker Rivian RIVN.O, said on Wednesday it has raised $500 million in a Series A funding co-led by Accel and Andreessen Horowitz.

The industrial robotics company was valued at $2 billion, according to a person close to the deal.

The funding, which is one of the largest Series A rounds for a robotics company, comes at a time when manufacturers are increasingly dealing with labor shortages and are under pressure to update aging production lines.

The Palo Alto-headquartered company is building a full-stack platform of foundation models, purpose-built robots and deployment infrastructure to automate industrial and manufacturing tasks at scale.

Accel partner Sameer Gandhi will join the company's board as part of the deal, which is expected to close later this month, and follows a $115 million seed round led by Eclipse Capital late last year.

Mind Robotics, founded by Rivian CEO and founder RJ Scaringe, was spun out of the EV company in November. Rivian operates as a partner and major shareholder, providing Mind Robotics with data for training its models and an environment to launch the technology.

The startup aims to address the gap in industrial automation by developing robots that can handle tasks requiring human-like dexterity, adaptability and physical reasoning.

Scaringe has said the company intends to focus on more traditional factory robot designs, rather than the much-hyped humanoid robots that have garnered significant attention.

Tesla TSLA.O and Nvidia-backed NVDA.O Figure AI are among many robotics companies that are building robots in a human-like form factor.

However, industry experts and executives have cautioned that commercializing advanced robotics remains a long road, as training the foundation models that power these systems demands vast amounts of data, a resource that is difficult to accumulate at scale.

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