Continuum + atomistic + process
Multi-physics foundation models
Models that learn the coupling between transport, thermodynamics, reaction kinetics, microstructure, and manufacturability.
Research at Shodh AI
Intelligence at the edge of physics.
We build foundation models, differentiable physics engines, and inverse-design systems for the hard industrial frontier: turning molecules, materials, and lab discoveries into scale-ready production.
4D
Digital twins across space and time
10M+
Synthetic physics samples under active modeling
100%
Customer IP isolation for sensitive chemistry
Research agenda
The core bets.
Targets into recipes
Differentiable inverse design
Optimization systems that work backward from yield, purity, throughput, stability, and cost constraints into practical process windows.
Synthetic data grounded in plants
Sim-to-real calibration
Closed-loop calibration pipelines that convert plant telemetry, microscopy, and experiment logs into better predictive physics.
Publications & briefs
Open technical work.
Available · Whitepaper
Bridging the Scale-Up Chasm
A technical overview of how differentiable physics and generative design can compress chemical and materials scale-up.
Open
In progress · Architecture report
Shodh AI V3.0 Architecture Report
A deeper systems paper on unifying quantum, atomistic, mesoscale, and continuum modeling inside one production-grade engine.
Open
Case study · Research brief
Factory-Calibrated Digital Twins
How process telemetry can tune simulation priors for reactor design, battery materials, and specialty chemical manufacturing.
Open
Research platform
From equations to factories.
Shodh AI research is not a paper exercise. Every model is evaluated against whether it can reduce pilot iterations, improve yield, or generate manufacturable process decisions.
Physics kernels
Differentiable solvers and learned operators for flow, heat, mass transfer, electrochemistry, and reaction systems.
Industrial datasets
Structured pipelines for microscopy, sensor telemetry, CAD, lab notebooks, and pilot-plant operating histories.
Generative CAD
Geometry and recipe generation constrained by manufacturability, safety, operating envelopes, and downstream validation.
Secure deployment
On-premise and air-gapped research workflows for customers with classified chemistry and production IP.
Next frontier
Research we want to make real.
We are looking for industrial partners, research labs, and frontier engineers working on problems where physics breaks at scale.
01
Publish scale-up and inverse-design benchmarks for process engineering.
02
Release partner case studies across specialty chemicals, batteries, and advanced materials.
03
Expand the foundation model to bridge molecular, mesoscale, and factory-scale physics.