Tools, Data & Consulting Services for A.I.-Driven Materials Design
- Automated machine learning modeling
- Analysis of data structure and features
- Optimization of processing procedures
- Screening millions of candidate materials
- Materials data repositories
- Custom data ingestion & scraping
- Management services
- Data infrastructure
- Domain expertise in materials modeling
- Highly flexible project structure
- Machine learning training
- Build internal machine learning efforts
Mateo JaramilloCEO and Co-Founder, Form Energy
The Aionics platform enables us to seamlessly implement machine learning models on our in-house data in real time, which brings another layer of rigorous analysis to help identify the chemical features driving performance that we care about most. The automated machine learning model-building and screening workflow also lets us screen hundreds of thousands of candidate materials for our devices in the blink of an eye.
A.I. Approaches Offer Significant Acceleration
0-6 months consulting
Deployment & Training
Development as requested
We seek to mitigate risk by combining high and low risk deliverables.
Machine learning-based performance predictions are considered high risk;
low risk deliverables include data management, candidate material scraping, historical data analysis.