Product
Run structured data experiments
Compare dataset variants, track quality metrics over time and identify which data configurations produce the best model outcomes.
Why it matters
Data experimentation as a first-class workflow
Most teams treat data preparation as a one-time step. LiteSeed makes it a structured, repeatable workflow — with versioned inputs, tracked outputs and comparable results.
Compare dataset variants
Run the same model on different dataset configurations and compare quality metrics side by side.
Track changes over time
See how quality scores evolve as you refine your Blueprint across generations.
Reproducible by default
Every experiment run records the exact Blueprint version and seed used.
Core capabilities
Experiment runs
Each experiment run generates a dataset from a specific Blueprint version and seed, recording all quality metrics for comparison.
- →Blueprint version + seed locked per run
- →Quality Score, row count and violation rates recorded
- →Run history with timestamps and metadata
- →Export any run's dataset for downstream use
Side-by-side comparison
Compare quality metrics, distributions and coverage across multiple runs of the same or different Blueprint versions.
- →Quality Score delta between runs
- →Field distribution comparison charts
- →Constraint violation rate trends
- →Coverage gap comparison across versions