Omnipresent Robotics to Acquire AGIBOT Robots for Michigan Deployment

May 13, 2026
Hyperscale Data’s subsidiary Omnipresent Robotics has signed an agreement with AGIBOT to purchase up to 143 intelligent robots for deployment at its Michigan facility, where the company will establish a robotics data collection center and expand its workforce.
Omnipresent Robotics to Acquire AGIBOT Robots for Michigan Deployment

Hyperscale Data, Inc. announced in a press release that its subsidiary Omnipresent Robotics has entered into an agreement with Singapore-based AGIBOT to acquire up to 143 intelligent robots. The arrangement formalizes an earlier partner agreement made in April 2026 and authorizes Omnipresent to resell AGIBOT products under its own brand.

The robots will support teleoperation, vision-language-action data processing, and embodied AI training. Omnipresent will also establish a robotics data collection center within Hyperscale Data’s Michigan facility, allocating about 100,000 square feet for robotics operations and workforce training.

The Michigan site is expected to function as the company’s U.S. hub for generating real-world robotics datasets and processing AI model data. Omnipresent plans to expand hiring across teleoperation, data labeling, engineering, and operational support as additional systems are deployed.

Hyperscale Data stated that the deployment will contribute to model training, industrial automation, and large-scale dataset generation for AI systems. The company noted that the facility’s existing infrastructure and location provide capacity for future expansion.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Robotics Brief, AI Funding Brief or Daily AI Brief.

Also, consider following us on social media:

AI & Robotics AI Funding News AI Brief AI Brief (X)
Free newsletter

AI Funding Brief

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.