Science has always been the bottleneck. Close the recursive loop, now.
Every material that changed the world took years of trial and error to find. Not because the answer wasn't there — but because experiments are slow, expensive, and sequential. SM-1 runs your material science and material engineering workloads autonomously, batteries included. Hypothesis trees. Millions of quantum-accurate simulations. Virtually validated engineering paths. Around the clock, without pause.
Solid-state crystal structures (including GNoME data)
Isolated molecular structures
Specialized datasets for battery technologies
Thermoplastics, thermosets, and commercial branded polymers
Steel, aluminum, titanium, copper alloys and more
Ceramics, glasses, composites, and semiconductors
01 Platform. Our AI material scientist designs, runs, and analyzes experiments inside virtual laboratories. Autonomously and at industrial scale.
Experiment Dashboard.Real-time tree exploration and session control
Watch SM-1 explore, branch, and synthesize findings in real time. Every experiment, measurement, and decision is visible as it happens.
GET ACCESSExperiment EngineAutonomous Hypothesis Exploration
SM-1 generates hypotheses, designs experiments to test them, and prunes dead ends automatically. Every decision is driven by measured data, not predictions.
Any AI Model
Swap providers without changing your experiments. The platform abstracts the model layer entirely.
Measurement-First Decisions
Every outcome is validated against real measurements. SM-1 only pursues directions backed by actual data.
Self-Directing Research
Between experiments, SM-1 evaluates progress, identifies gaps, and generates follow-up questions without prompting.
Virtual Laboratories.Closed-loop experiment environments at industrial scale
Phase diagram lookups, mechanical property measurements, microstructure analysis. All inside virtual lab environments. The environment is the reward signal: nature itself, not math graders.
Autonomous Sessions.Continuously-alive research lifecycle
Sessions run for days or weeks without interruption. When SM-1 finishes its current work, it pauses, evaluates what it has learned, and resumes with new directions. You go home. SM-1 keeps working.
100+ hypotheses tested and 61 experiments run in a single investigation. SM-1 explores deeper than any human team.
Switch between providers freely. Your experiments and results stay the same regardless of the underlying model.
Survives disconnects, restarts, and downtime. Always picks up exactly where it left off.
02 SM-1. What Our AI Material Scientist Can Do
01 Discover New Materials.
785,000+ material entries across crystals, molecules, and electrodes. SM-1 identifies promising candidates you'd never find manually.
02 Simulate Before Synthesizing.
Every candidate is deployed into a high-fidelity physics environment first. Behavior is validated under real-world conditions before any physical experiment.
03 Bridge Quantum to Multiscale.
From atomic electronic structure to grain boundaries to bulk mechanical performance — a single investigation spanning every scale without losing resolution.
04 Deliver Validated Results.
Every finding backed by quantitative measurements. Dead ends automatically eliminated. Reproducible, publication-ready conclusions.
Multi-Scale Fluency.From atoms to structures, in a single investigation
A change at the atomic level cascades through microstructure into macro-scale properties. Human researchers specialize in one scale. SM-1 works fluently across all three simultaneously.
HumanRequires massive supercomputers for small clusters.
SM-1Models entire complex systems with quantum accuracy.
HumanUses SEM/TEM images to guess properties.
SM-1Perfectly predicts grain boundaries and stress points.
HumanRelies on safety factors and over-engineering.
SM-1Designs optimal structures with zero wasted material.
No Black Box.Every decision is traceable
Every hypothesis explored, every experiment run, every candidate compared. The full chain of reasoning is visible. If a result looks unexpected, you have everything you need to verify it yourself.
Your Role Shifts
Manually running experiments
Validating and curating AI-generated findings
Guessing which directions to explore
Asking the AI to explain why something works
Limited by human intuition
Discovering new laws hidden in complex data
No Lab Required.Predict, iterate, and optimize entirely in silico
Every stage of the research cycle — prediction, iteration, multi-path exploration, cost optimization — happens inside SM-1's virtual laboratories. No physical manufacturing. No waiting for lab time. No destroyed samples.
Prediction Without Manufacturing
Material properties — yield strength, ionic conductivity, band gap, thermal stability — are predicted from first principles before a single gram is synthesized. Physical testing becomes confirmation, not discovery.
Iterative Design Without a Lab
SM-1 runs design iterations at the speed of compute, not the speed of lab scheduling. A design cycle that would take months of physical prototyping completes in hours. Failure is free.
Parallel Hypothesis Exploration
Where a human team explores one or two candidates at a time, SM-1 evaluates hundreds simultaneously — branching, pruning, and converging on the strongest directions in a single session.
Cost-Efficient Optimization
Compute scales with problem complexity. Routine evaluations are cheap. Hard problems get more resources. The result is orders-of-magnitude lower cost per validated candidate compared to physical R&D.
Adaptive ComputeMore compute on harder problems, less on easy ones
Hard problems get more compute. Easy ones resolve fast and cheap. SM-1 decides when to explore broadly vs. dive deep, adapting in real time to what the experiments reveal.
TRY THE ENGINEWe reward SM-1 for finding what we don't know, not for being sure of what we already do.
Most decisions are made from experiment results. AI reasoning only kicks in when the data is ambiguous.
Harder problems automatically get more compute. Easy ones resolve fast and cheap.
Start small. Scale up when you need to. The platform adapts to your requirements.
03 Research. Publications and Working Papers
How we're building our AI material scientist that autonomously designs and runs experiments. From virtual laboratories to materials discovery at industrial scale.
LEARN MORE