Physics-Informed AI.

Delivering Equivariant Intelligence for industrial systems across all data modalities.
Unifying Signal Processing, Geometric Deep Learning, and Semantic Geometry.

Vision & Signal ->

Physics-informed models for high-dimensional data.
Core: Geometric Deep Learning and Scattering Transforms for Euclidean (grids) and Non-Euclidean (graphs/manifolds) data.

SymLogix™ ->

Deterministic NLP for high-stakes industrial logs.
Core: Mapping text to Semantic Manifolds using Spectral Graph Theory. Verifiable meaning detection that is invariant to vocabulary.

Education ->

Specialized curriculum for industrial R&D teams.
Core: Geometric Deep Learning, Graph Neural Networks (GNNs), and Physics-Informed and SOTA deep learning architectures.