Research
Introducing Schema
Data Language Model for AI Training on Tabular Data
We present Schema, Data Language Model that natively understands tabular data.
Schema represents a departure from existing approaches that serialize tables into text or require extensive preprocessing pipelines. Instead, it directly comprehends the structure and semantics of CSVs, spreadsheets, databases, and embedded tables: enabling AI model training on raw data without transformation.
How It Works
Data to Deployed AI Models in 3 Steps
No preprocessing required. Schema handles tabular data so you can focus on AI development.
Connect or Generate Data
Choose your data strategy. Your data is encrypted and never leaves your control.
- Direct database connections
- Synthetic data generation
- Data auto-sync
- Data preview and validation
Configure & Train
Select your datasets, data-sync strategy and build AI models on schema-v0 instantly.
- Automatic feature engineering
- Model architecture selection
- Multi-source dataset selection
- Real-time training metrics
Deploy & Iterate
Test your models in playground, evaluate metrics, and deploy endpoints.
- Interactive testing playground
- Performance evaluation
- One-click endpoint deployment
- Continuous model updates