MIOS
Material Intelligence Operating System
Discover and validate new alloys, in plain English.
MIOS turns material selection from months of trial-and-error into a research-grade query. Tell it what you need, “a corrosion-resistant alloy for 800°C turbine service with fatigue life >10⁷ cycles”, and it searches the known materials space, runs validated ML models, and ranks candidates by performance and confidence.
Databases
MPDS · AFLOW · Materials Project · internal
Models
CrabNet · ALIGNN · Roost
Validation
Physics-based cross-checks
Deployment
On-prem · cloud · hybrid
6 to 18 months
Developing or qualifying a new alloy traditionally takes 6 to 18 months of experimental iteration, with no audit trail behind the final decision. MIOS compresses the discovery loop and makes every recommendation reproducible.
From input to outcome
Natural-language intent
State your constraints in plain English. MIOS extracts structured targets, composition limits, temperature, fatigue, cost, corrosion class.
Multi-database search
Queries MPDS, AFLOW, the Materials Project and your internal data to assemble candidate space.
Validated ML inference
Runs CrabNet, ALIGNN and Roost property models, then applies physics-based cross-validation on every prediction.
Ranked, traceable output
Returns Pareto-optimal candidates with uncertainty bounds, the models that ran, the data used, and a reproducible decision hash for audit.
What MIOS does
Plain-English constraints
No query language. MIOS parses engineering intent into structured material targets automatically.
Physics cross-validation
Every ML prediction is checked against physical priors, no black-box numbers.
Uncertainty on everything
Confidence bounds accompany every property so you know what to trust and what to test.
Reproducible decision hash
Each recommendation carries an audit hash: which models, which data, fully reproducible.
Internal data fusion
Blend public databases with your proprietary test data for context-aware results.
Pareto trade-off view
See the full performance-vs-cost-vs-risk frontier, not a single opaque answer.
10×
faster candidate screening
100%
traceable recommendations
3
validated ML model families
Use cases
Common situations where MIOS earns its place on day one.
- Corrosion-resistant alloys for high-temperature service
- Lightweight high-strength alloys for aerospace structures
- Cost-down substitution of strategic / scarce elements
- Qualification support with full audit traceability
See MIOS on your own parts and data
We start with a focused study of your process, then show MIOS working against your real workflow.