Data Quality#
Ensure high-quality synthetic data generation with comprehensive validation and evaluation tools in NeMo Data Designer. Validate generated code for correctness and assess overall data quality using automated metrics and LLM-based judges.
Quality Assurance#
Implement quality controls and assessments to maintain high standards for your synthetic data outputs.
Code Validation
Generate and validate code in multiple programming languages including Python and SQL with static analysis and quality checks.
Data Evaluation
Assess generated data quality using LLM-based judges, custom rubrics, and automated evaluation reports.
Add Custom Validation
Integrate custom validation endpoints to validate generated data using your own validation logic and external services.