Turn raw measurements into clean, AI-ready datasets. We identify hidden trends, fill in missing data, and train predictive models for property estimation, optimization, and quality control.
Capabilities
- Normalize and clean legacy data records
- Handle missing values with robust imputation algorithms
- Develop predictive models with rigorous validation
Example Applications
- Structure internal datasets run by different researchers by resolving units, labels, and outliers
- Identify critical variables affecting properties with feature importance analysis