Qingyan Precision / 清研精准

Summary

About

About Qingyan Precision / 清研精准

Qingyan Precision develops data and evaluation infrastructure for physical AI in industrial and new-energy settings. Its systems collect multimodal observations from real equipment, organise them into governed data assets and create training and evaluation sets for embodied models.

The stack covers sensors, synchronisation, annotation, validation, skill libraries and world-model tooling. Engineering environments reproduce industrial processes so robot policies can be measured against repeatable tasks before deployment. Qingyan works with manufacturers and model developers that need domain-specific data from factories, energy equipment and other structured physical operations.

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Articles

Funding

Investors

  • BAIC Capital - Lead - VC - 1 funding event - first seen 2026-06-24
  • Beijing Green Energy Fund - Lead - VC - 1 funding event - first seen 2026-06-24
  • Yulon Group - Participant - Angel / Individual - 1 funding event - first seen 2026-06-24

Timeline

Events

  • 2026-07-13 - Funding - Qingyan Precision discloses completion of two June B-series financings

    The July announcement is a later disclosure of two rounds completed in June and is not treated as a third financing or a new numeric amount. Automotive industry investors named across the B2 and B3 rounds include BAIC Investment, Xingyuan Capital, FAW Fusheng, Great Wall Capital, Shaanxi Auto Capital and Yulon Group. Qingyan Precision positions the capital behind an industrial Physical AI engineering base spanning real-factory data, validation, compute and embodied-robot workflows.

    Source
  • 2026-06-24 - Funding - Qingyan Precision closes several-hundred-million-yuan B3 financing

    The round was led by Beijing Green Energy Fund and BAIC Capital, with Yulon Group participating. Funding is allocated to talent, multimodal data-collection equipment, compute, model training and Physical AI engineering infrastructure. Qingyan Precision positions its stack around industrial data capture, validation, evaluation sets and brain-inspired world-model tooling.

    Source