Industrial Foundation Model (IFM) Architecture
Layered from L0 (First Principles) to L4 (Applications). The L2 Equipment Surrogate Model core ensures all models are physically trustworthy, composable, and scalable.
Physics-Informed ML · Equipment Surrogate Models
Embedding physical laws into deep learning. Delivering high-fidelity models in weeks using dozens of samples — not the thousands and years required by traditional AI.
LLMs are statistical models. Industrial systems are governed by physical laws. Porting LLMs to the factory floor faces fundamental barriers.
LLMs can't guarantee outputs comply with physical laws. In safety-critical scenarios, a "plausible" suggestion violating thermodynamics can be catastrophic.
Industrial processes are governed by PDEs/ODEs. LLMs process discrete tokens and cannot solve continuous fields or meet millisecond real-time control demands.
Layered from L0 (First Principles) to L4 (Applications). The L2 Equipment Surrogate Model core ensures all models are physically trustworthy, composable, and scalable.
Core Product
Pre-trained "gray-box" AI models with embedded physical constraints. Each ESM is a reusable, scalable model of a specific unit operation.
Few-Shot Samples
Dozens of data points
Simulation + Physics-Informed ML
High-Fidelity ESM
+ Parameter Identification
Compresses hours of physics simulation into milliseconds, enabling real-time monitoring and Advanced Process Control.
Embeds physical equations (PIML) to reverse-engineer unknown parameters from sparse data. Explainable equipment health diagnostics.
Pre-trained on general physics. New site deployment requires only dozens of samples for calibration via transfer learning.
Rigorously benchmarked against classic deep learning and hybrid AI on complex industrial data.
+700%
From failed models to highly predictive assets on unseen test data.
-52%
High-fidelity prediction of entire process curves using only the first 5-10% of data.
Classic AI Models
ThinkMachine ESM
White: ground truth · Color: model prediction · Real-time animation
Model Library
First-principles ESMs pre-trained on simulation data. Ready to combine and fine-tune for your specific process.
Deploying ESM capabilities as high-value solutions through few-shot fine-tuning.
We invite industry partners — production managers, process experts, and site engineers — to validate and expand the Physics-AI paradigm.
The complexity of the physical world is no longer a barrier to innovation.
Schedule Meeting →