Gretel

What is Gretel?

Gretel.ai is a platform that helps developers create synthetic data — artificial datasets that capture the statistical patterns of real data without containing sensitive personal information. It is used in sectors such as finance, healthcare, and government, where privacy is a priority.

The platform uses AI to learn the statistical patterns in your existing data and generate anonymized output, so personal or sensitive details are removed while your original data stays private. Beyond generation, Gretel provides APIs for fine-tuning AI models, evaluating data quality, and collaborating with your team on cloud projects.

Who created Gretel?

Gretel was created by Alexander Watson, the company’s CPO and Co-Founder. It is a synthetic data platform built for Generative AI, providing APIs that create anonymized, safe synthetic data for training and improving models while maintaining privacy. The company focuses on enterprise AI, producing high-quality synthetic data for industries including finance, healthcare, and the public sector.

What is Gretel used for?

Key capabilities include:

• Synthetic data generation — create artificial datasets that mimic your real data, fully anonymized.
• Custom AI models — fine-tune models to your specific needs using Gretel’s APIs.
• Data pipelines — build workflows for data processing and transform data with flexible rules.
• Quality and validation — measure the quality of synthetic data and validate models with scores.
• On-demand generation — produce synthetic data whenever needed, with on-premises data retention available.
• Cloud scaling and collaboration — handle larger workloads and work on shared projects with your team.
• Gretel Navigator — a tool for data generation and pipeline building.

Who is Gretel for?

Gretel suits developers building with synthetic data, data scientists and data engineers working on pipelines and data quality, AI and machine learning engineers refining models, and AI researchers. It also fits finance, healthcare, and public sector professionals who need secure data for analysis, as well as privacy and compliance professionals responsible for data protection. Teams that collaborate on data projects can use its shared cloud workflows.