Generation
Data Assimilation
Integrate real-world observations with generative models to produce synthetic data that faithfully reflects source distributions.
Grounded in Reality
Multi-Source Fusion
Combine data from heterogeneous sources while resolving schema conflicts and maintaining referential integrity.
Distribution Alignment
Align marginal and joint distributions so that synthetic outputs match observed statistics across all dimensions.
Incremental Updates
Assimilate new data incrementally without retraining from scratch, keeping models current as observations evolve.
