Gretel

At Gretel.ai, the core belief is that privacy is a problem rooted in code, not just compliance. This philosophy drives an obsessive quest for elegant, composable abstractions that enable scalable and flexible data sharing. Gretel empowers developers and data scientists to build with data, together, by providing a platform for creating high-quality, safe synthetic data. This synthetic data mirrors the statistical properties of real-world datasets without exposing sensitive information, thereby unlocking the value of data while upholding stringent AI and data privacy standards. The company's mission is to solve one of the most pressing challenges in AI: access to high-quality, privacy-preserving data. This need was identified by the founders through their extensive experience in security, AI, and data infrastructure, recognizing that companies often struggle to balance data accessibility with security. Instead of creating another data management tool, Gretel focuses on synthetic data as the key to unlocking AI's full potential.

Gretel fosters a developer-first culture, designing its privacy-preserving synthetic data tools with accessibility and transparency at the forefront. Developers can interact with Gretel's platform through a cloud-native console, a command-line interface (CLI), or a software development kit (SDK). A free 'developer' plan ensures that access to its privacy engineering tools is available from day one, encouraging widespread adoption and experimentation. Transparency is further emphasized by Gretel's open-source core, which allows developers to inspect and contribute to its privacy-preserving data technologies. The company operates as a fully distributed team, with employees across the U.S. and Canada, reflecting a modern approach to work that values freedom and talent regardless of location. This commitment to innovation and a supportive, forward-thinking culture has attracted significant investment and a rapidly growing user base, including Fortune 500 companies. Gretel is dedicated to building the product they always wished they had, one that accelerates AI innovation while maintaining robust privacy compliance.