Product
Reproduce every dataset experiment
Make synthetic data workflows deterministic and repeatable, so teams can compare results with confidence.
Why it matters
Isolate data from model changes
When a model performs differently across training runs, teams need to isolate whether the change came from the model or the data. LiteSeed guarantees that the same Blueprint and seed always produce the same dataset — bit for bit.
Isolate variables
Know whether a model change or a data change caused a performance difference.
Audit trails
Every dataset version records the seed and blueprint hash used to generate it.
Confident benchmarking
Run benchmarks against a fixed dataset that can always be regenerated identically.
Core capabilities
Deterministic seeding
Every generation run is seeded with a user-defined integer. The same seed + Blueprint always produces the same output — regardless of machine, time or environment.
- →Seed stored in dataset version metadata
- →Blueprint hash computed and stored at generation time
- →Re-run any historical dataset with one click
- →Seed 42 is the default for quick reproducibility
Blueprint versioning
Blueprints are versioned documents with parent-child lineage. Every change creates a new version, preserving the full history of schema evolution.
- →Immutable Blueprint versions — no silent schema drift
- →Parent-child lineage for tracking schema evolution
- →Version diff to compare field changes across versions
- →Rollback to any previous Blueprint version
Dataset version registry
Every generated dataset is stored as a versioned artifact with full provenance metadata.
- →Blueprint ID + version + seed = complete provenance
- →Row count, file size, format and quality score recorded
- →Dataset versions linked to experiment runs
- →Export any version in CSV, JSONL or Parquet