Solving Hard Problems
Starts Here.
Most AI platforms break at multiscale complexity.
Ours was built for it – accelerating development of complex physical systems, shrinking iteration cycles, optimizing manufacturing processes, and getting engineering breakthroughs to production – fast.
Book Demo
The Hard Problems We’re Built to Solve — Fast.
Manufacturing Process Optimization
Scale R&D to production faster by rapidly identifying optimal process recipes and optimizing high-dimensional process inputs in real time using available data.
Materials Discovery and Property Optimization
Accelerate materials development optimizing for target performance with the fewest experimental and simulation cycles.
Simulation Acceleration and Optimization
Speed up high-cost simulations, reduce design iterations, and explore more of the solution space with fewer trials.
The MIND Platform: Built for Engineering Complexity
An integrated platform that combines domain knowledge, simulation, ML, and GenAI
to solve your toughest problems at scale.
Data Catalog
Locate, filter, and structure domain-specific data from fragmented sources—ready for simulation, modeling, or training.
Machine Learning
Build interpretable models that reflect real-world physics and variability—using domain-aware ML, not just curve fitting.
Optimization
Navigate tradeoffs across 1,000s of variables with multi-objective optimization tailored to engineering constraints - from R&D to manufacturing yield.
Active Learning
Continuously improve models by targeting the most informative data—especially in sparse or evolving environments.
Inverse Solver
Work backward from performance goals to derive input combinations—built for inverse design in complex physical systems.
App Hub
Rapidly build and deploy custom engineering apps—modular, scalable, and integrated into real workflows from day one.
Why Multiscale Works When Others Don’t
We don’t just model forward—we start with the outcome you want and work backwards to get there. Our approach blends physics, data, and decision logic to solve engineering problems others can’t touch.
Proof, Not Promises
Hard numbers. Real savings. From real customers slashing test cycles, cutting simulations, and improving yield.
From 10X reduction in testing stages
With <10% loss in accuracy
50% in physical trials
Solving Multiscale Challenges
Across Every Engineering Vertical
Semiconductors
Analyze die-level test data, predict overlay drift, and optimize yield with physics-informed AI – from early design to fab-scale production.
Automotive & EV
Optimize high-dimensional designs under performance constraints using AI-driven topology modeling. Qualify new materials faster with high-throughput screening for new product development.
Aerospace
Design lighter structural components and improve production yield by reducing physical testing and part variability.
Metals & Materials
Correlate process inputs with material properties, optimize yield, and accelerate alloy development with fewer experimental cycles.
Chemicals & Polymers
Combine AI with molecular simulations to explore formulations, reduce validation cycles, and optimize processing conditions.
Energy & Utilities
Model complex energy systems, optimize control strategies, and validate digital twins with AI-augmented simulation.Solving Hard Problems Starts Here.
Let’s solve your’s next. From simulation bottlenecks to process variability and yield loss — tell us what you’re up against. We’ll dig in together.
