Gretel (https://www.gretel.ai) is a generative AI platform for creating multi-modal synthetic data on-demand. Use Gretel to automatically fine-tune custom AI models and generate synthetic data that's as good or better than data you already have.

Gretel has four core APIs--Synthetics, Transform, Classify, and Evaluate--that can anonymize sensitive datasets and create high fidelity synthetic versions that are statistically accurate, infinitely scalable, privacy protected, and safe to share. Gretel enables multimodal synthetic data generation with enterprise-grade features that validate data accuracy to avoid hallucinations, ensure privacy protection of sensitive datasets, and enable data generation at scale.

• Leverage the power of Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Diffusion Models to generate synthetic data for any tabular, unstructured, time-series, relational, and image data sources. Built-in privacy filters allow for flexible configuration of privacy-enhancing techniques such as one-click outlier and similarity detection, overfitting prevention, and tunable differential privacy settings.
• Anonymize your data with privacy-preserving techniques using advanced AI-capabilities to create accurate data for building realistic pre-production systems. Custom predictors and field transformations with regular expressions add additional power and control to workflows.
• Automatically and continuously detect and label sensitive data wherever it resides using best-in-class Named Entity Recognition (NER) and Natural Language Processing (NLP) to provide instant analysis of accuracy and metadata.
• Rapidly validate the quality and utility of your synthetic data with accuracy and privacy metrics and customizable reports.