Use Case
Simulate rare events for robust models
Generate training data that includes the edge cases and rare scenarios your model needs to handle — even when they almost never appear in production data.
Start FreeThe challenge
Models fail on rare events because they never trained on them
Fraud, medical emergencies, system failures and other rare events are underrepresented in production data — but they're exactly the scenarios where model failures are most costly. LiteSeed lets teams explicitly inject rare event scenarios into training data at configurable rates.
Configurable injection rate
Set the exact frequency of rare events in generated training data — from 0.1% to 50%.
Semantically coherent rare events
Rare event rows maintain logical consistency with the rest of the dataset — not random noise.
Reproducible rare event sets
The same seed always produces the same rare event distribution for consistent benchmarking.
How LiteSeed helps
Rare event distribution
LiteSeed's rare_event distribution type generates rows that represent low-probability scenarios with configurable frequency.
- →rare_event distribution type in Blueprint field definitions
- →Configurable frequency: 0.1% to 50% of generated rows
- →Mixture distributions for multi-modal rare event scenarios
- →Edge case injection in Training mode
Semantic coherence for rare events
Rare event rows maintain logical consistency with the rest of the dataset — ensuring models learn the right patterns.
- →Cross-field semantic consistency for rare event rows
- →Domain vocabulary anchoring for rare event scenarios
- →Constraint enforcement for rare event rows
- →Quality scoring for rare event row validity