The Skanda
Protocol
The Universal "Matter Compiler" for Mesoscale Manufacturing.
1. The Thesis: Solving the
"Missing Middle"
Atomic AI
GOOGLE GNoME
Good at finding molecules. But molecules don't build batteries on their own.
The Mesoscale
SHODH AI / SKANDA
Pores, Grains, Defects. The structural regime where manufacturing actually fails.
System AI
ANSYS / CAD
Good at simulating cars and planes, but blind to the material physics inside.
"In a Gigafactory, yield loss is almost never an 'atomic' problem; it is a structural problem. If you control the structure, you control the yield."
2. The Engine:
3D Diffusion Transformers
To solve the scale-up problem, we cannot use traditional AI that just predicts a number. We need AI that designs the solution.
We utilize a 3D Diffusion Transformer (DiT)—the same core architecture behind OpenAI’s Sora, but retrained for Physics. Instead of pixels, Skanda treats matter as 3D Voxels.
It learns the "grammar" of how particles pack, pores connect, and binders stretch.
Architecture Spec
3D Voxels
Volumetric data representing density and porosity.
DiT (Diffusion Transformer)
Generative design capable of handling complex topology.
FNO (Fourier Neural Ops)
Validates designs in milliseconds vs. hours in traditional solvers.
3. The Universal Brain
We don't build a new AI for every material. We built a Universal Brain that understands geometry, and we plug in "Physics Cartridges."
Energy Cartridge
Teaches the AI how ions navigate battery pores.
Fluid Cartridge
Teaches the AI how gas bubbles escape porous media.
Mechanics Cartridge
Teaches the AI how metal grains slip under stress.
The Network Effect:A "clogged pore" in a battery is mathematically identical to a "clogged pore" in a hydrogen filter. By solving one, Skanda gets smarter at all of them.
Skanda-Morph Engine
Simulating Shear, Crush, Deform...
4. Skanda-Morph:
The Process Compiler
The fatal flaw of Lab AI is the assumption of "Perfect Geometry." But manufacturing is violent—it shears, crushes, and deforms matter.
Digital Twin: Simulates the Rheology (mixing) and Calendering (crushing) of the material.
Zero-Shot Manufacturing: It doesn't just give you a 3D design; it gives you the factory settings to build it.
5. The Data Moat:
The Physics Hypercube
"We don't wait for data from slow labs. We manufacture our own data."
10M+
Synthetic Simulations
We taught our AI the fundamental laws of physics (Thermodynamics, Stress-Strain) before it ever saw a real battery.
Sim2Real
CT Scan Calibration
We use X-ray CT scans of real manufactured parts to "calibrate" the AI, teaching it the messy reality of factory humidity and gravity.
6. The Neural Edge:
Decentralized Compute
Industrial AI cannot live in the cloud. A production line moving at 50m/min requires microsecond decisions.
Skanda-Edge Nodes
Powered by NVIDIA Orin/IGX. Deployed directly on the production line for real-time inference.
Federated Learning
The AI learns from local defects and sends only the math (Gradients) to our central brain. Raw proprietary data never leaves the factory.
Compute-per-GWh
"In the age of Software-Defined Materials, Yield is a function of Edge Compute."
Interactive Demo
The Bottom Line
Shodh AI is moving the industry from
Discovery by Luck to Discovery by Design.