Physna Unveils 'Physical AI' Search and Opens Access to Select Partners to Supercharge 3D Parts Data Training
Physna is licensing API access to its Physical AI search and normalization engine for a cohort of AI labs, OEMs, industrials, and frontier tech companies.
COLUMBUS, OH, UNITED STATES, January 13, 2026 /EINPresswire.com/ -- Physna, the leader in geometric deep-tech, today announced the launch of its new Physical AI search and a limited early-access program that enables select AI and technology companies to radically accelerate model training on their own 3D product data.
For the first time, organizations can train models directly on normalized geometry - the representation that captures orders of magnitude more usable signal than images, text, or unaligned 3D formats.
Unlocking 10,000× More Training Signal From 3D
Most AI systems today still learn from text, 2D images, or noisy 3D scans and meshes. These data types are weak approximations of the physical world - missing structural, functional, and manufacturability information that real-world systems need. Physna changes that.
The platform converts CAD, scans, meshes, and point clouds into canonical, orientation-invariant, topology-consistent geometry. Models trained on this normalized geometry receive on the order of 10,000× more effective training signal per sample compared to training on raw, unnormalized 3D.
On an information-equivalence scale, that translates to approximately:
~1,000,000× vs 2D images
~1,000,000,000× vs text
(Estimates refer to relative usable information for AI training - not literal file size.)
The Foundation for Real-World AI
With Physna-normalized 3D, AI models begin learning physical concepts that were previously out of reach: structural and functional similarity across part families manufacturability and cost patterns directly from shape assembly and interoperability relationships supplier and variant equivalence geometric semantics without manual labels.
These capabilities are critical for next-generation AI in robotics, manufacturing, design, supply chain, aerospace, and defense - domains where models must understand how real things are shaped and how they fit together.
Selective Access for High-Impact Builders
Physna is now licensing API access to its Physical AI search and normalization engine for a limited cohort of AI labs, OEMs, industrials, and frontier tech companies.
“This is the missing training signal for the physical world of AI,” said Paul Powers, Physna CEO. “Teams building robotics models, factory automation, digital twins, or multimodal systems can now learn from the geometry itself - not the noisy approximations. The companies that adopt this first will shape the next decade of real-world AI,” he added.
Organizations interested in joining the invite-only early access program can contact Physna to begin exploring accelerated training on their proprietary 3D datasets at https://www.physna.com/
About Physna
Physna is the leader in Physical AI. Its geometry engine transforms 3D data into normalized, machine-ready representations that unlock deeper understanding of how parts are shaped, how they function, and how they fit together. Physna powers next-generation AI for robotics, manufacturing, defense, supply chain, and design. Learn more at https://www.physna.com/
Keith Newman
The GTM Firm
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