Gretel Evaluate

Validate the quality of
your synthetic data with comprehensive evaluation.

Quick synthetic data evaluation for the metrics you care about.
Validate your synthetic data with comprehensive, customizable reports.
What is Evaluate?

Understand your data with synthetic data evaluation.

Gretel Evaluate provides an out-of-the-box report on every model you train, so you can easily understand how your data performs on key metrics and compare results side by side.

  • Synthetic Data Quality Scores (SQS)

    Measure how closely the generated data maintains the statistical properties of the original dataset.

  • Privacy Protection Levels (PPL)

    Show the tunable privacy levels of each synthetic model.

  • ML Quality Scores (MQS)

    Assess the performance of synthetic data on classification and regression models.

  • Gretel Benchmark

    An easy-to-use low-code tool that benchmarks multiple datasets against multiple synthetic models.

Benefits for Developers.

  • Eliminate evaluation bottlenecks. Accelerate model development with faster data feedback loops.

  • Improve data comprehension. Get a deep understanding of the technical metrics that matter most in your data.

  • Increase operational efficiency. Easily compare synthetic models and datasets throughout the ML lifecycle.

Tabular Data Quality

Verify data meets quality standards.

  • We do the heavy lifting. Gain rapid insight into your synthetic data performance with a high-level composite Synthetic Data Quality Score (SQS).

  • Review data quality. Synthetic data evaluation ensures your sis as good—or better than—real-world data with statistical assurance verified with Principal Component Analysis (PCA).

  • No data field is overlooked. Correlation between every pair of fields is computed and compared between real-world training data and generated synthetic data.

Tabular Data Utility

Analyze data accuracy and performance.

  • At-a-glance reporting on data utility. See how your synthetic data compares to real-world data with a Machine Learning Quality Score (MQS).

  • Data analysis you can trust. Synthetic and real data are trained and evaluated on AutoML classification and regression models and the top models are compared.

Text Data Quality

Verify data meets quality standards.

  • Deploy synthetic text data confidently to train downstream  applications.

  • Gain a holistic understanding of text semantic and structural similarity with easily digestible metrics.

Gretel Benchmark

Benchmark model performance.

  • Track experiments or monitor data drift by comparing multiple models and datasets with just 5 lines of code.

  • Get valuable measurements like Synthetic Data Quality Scores (SQS), dataset statistics, and training time all in one place.

Get Started

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