Gretel Navigator Fine Tuning

Create high-quality, domain-specific datasets for generative AI

Gretel’s flagship model for generating tabular datasets supporting numerical, categorical, free text, and event-driven data.
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Key benefits

Generate high-fidelity synthetic data without compromising privacy.

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  • Strong privacy guarantees

    Protect sensitive entities in the training dataset without compromising usability.

  • Flexibility

    Leverage an LLM-based system to handle complex tabular datasets all in one job.

  • High-quality

    Use a pre-trained transformer-based model to deliver best-in-class data fidelity.

  • Simplicity

    Configure with YAML quickly, with defaults that work well for diverse datasets.

How it works

Preserve data-type nuances and relationships in complex enterprise datasets.

Navigator Fine Tuning (NavFT) is an LLM-based AI system engineered to support tabular datasets with diverse modalities. Observe how it effectively learns patterns to generate high-quality, realistic data without replicating original data, ensuring robust privacy protection while preserving data utility and integrity.
Numerical data
Categorical data
Free text data
Mix of tabular modalities

Resources

Navigator Fine Tuning is Now Generally Available
Synthesizing Private Patient Data with Gretel: A Step-by-Step Guide
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