Gretel AI offers a SaaS platform (with API access) that lets engineers create anonymized synthetic datasets from real data for analytics and model training, reducing the risk of leaking personal or sensitive information. The product is currently in beta and the company aims for general availability later this year. Gretel’s tooling is designed to be low-friction for engineers (simple datasets can be created in as little as 10 minutes; complex cases such as genomic datasets can take several days) and can also augment or fill gaps in real-world data. Early customers span life sciences, financial services, and gaming, reflecting enterprise demand for privacy-preserving data tooling. The three co-founders (Ali Golshan, Alex Watson, and John Myers) built the company out of experience in cybersecurity and cloud services. Financially, the company has raised $65.5 million to date and this fundraise implies a valuation in the $320–$350 million range. Gretel positions itself as a developer-focused, tech-agnostic solution to help companies implement privacy by design across data pipelines. Gretel builds an open-source synthetic machine-learning library that trains models on sensitive data while enforcing differential privacy to produce anonymized, shareable artificial datasets. The product is aimed at developers who need faster, more reliable ways to anonymize data for testing and feature development. This year the company focused on developing the open-source product and building a community around it. Gretel plans to offer a SaaS service to generate synthetic and anonymized data at scale. The company was founded last year and is led by co-founder and CEO Alex Watson, a former AWS GM. Gretel has no paying customers yet and expects to begin taking in revenue next year; it has raised $15.5 million to date, including a $12 million Series A. Gretel is building software that enables developers to automatically check out anonymized, synthetic versions of sensitive datasets for safe collaboration. The platform uses machine learning to categorize and label data elements (names, addresses, identifiers) and applies differential privacy to produce entirely fake datasets that behave like real user data. Founders include Alex Watson, John Myers, Ali Golshan and Laszlo Bock, and the team includes engineers with backgrounds at the NSA, Google and AWS. Gretel plans to ramp up engagement with the developer community and make the platform available within roughly six months. The company raised $3.5 million in seed funding to get the platform off the ground. It intends to charge customers on a consumption-based pricing model similar to cloud providers.

Total raised

$66M

Funding rounds

3

Latest round

Series B

Latest activity

Oct 2021