Inbolt CEO to Challenge AI Data Consensus at RoboBusiness Conference

Rudy Cohen, co-founder and CEO of Inbolt, will address the RoboBusiness conference on October 20 in Santa Clara, California, to challenge the prevailing industry narrative on artificial intelligence. Cohen intends to argue that the primary obstacle facing physical AI is not a shortage of data, but rather the complexities of real-world deployment.

Speaking in a session titled “Physical AI Doesn’t Have a Data Problem; It Has a Deployment Problem,” Cohen will focus on the critical loop between perception and motion. He will highlight the high "integration tax" associated with deploying AI in industrial settings. To support his thesis, Cohen plans to present production data from major automotive manufacturers to illustrate where physical AI delivers tangible commercial value.

The Industrial Reality

Inbolt, founded in 2019, specializes in providing a real-time control layer and 3D vision for industrial robots. This technology allows machines to adapt to their surroundings in real-time, effectively turning digital twins into live robot execution. By doing so, the company aims to reduce the reliance on expensive physical fixtures and complex wiring typically required during factory automation setup.

The company's approach is already active in the field. Inbolt has deployed its vision-guided control across more than 100 factories, recording over 40 million robot cycles. This technology is currently utilized on production lines at major automotive firms, including Ford, Toyota, and Stellantis.

Shifting the Bottleneck

This perspective marks a significant departure from the "lab" approach common in the robotics industry, which typically prioritizes the scaling of AI models and the collection of massive datasets. Cohen’s argument shifts the focus toward the "factory" reality, where stability, cycle time, and the cost of integration are the actual barriers to widespread adoption.

If the primary bottleneck is indeed deployment rather than data availability, the path to commercial viability for physical AI changes. It suggests that the industry must prioritize improving the hardware-software integration loop and lowering the costs of installation to see meaningful growth in industrial automation.

Future Outlook

As the industry watches the results of these deployments, the focus will likely shift toward how companies can further reduce the integration tax. While Inbolt continues to scale—having recently raised a €15 million Series A round in September 2024—the broader question remains whether other AI firms can pivot from data-centric models to deployment-centric strategies to achieve similar success in the automotive and manufacturing sectors.