What problem does Gretel solve?

Gretel aims to address the central problem of data bottlenecks that hinder innovation within teams and organizations. These bottlenecks arise from data silos with strict access controls and lengthy approval processes for accessing production data. Gretel believes that by providing the right tools to create safe versions of data, these bottlenecks can be removed, enabling faster data sharing, access, and ultimately, accelerated innovation, product development, and problem-solving.

The data bottleneck problem manifests in three tiers, each corresponding to specific use cases encountered by potential users:

1. Expanding access to datasets that are currently limited to a subset of teams.
2. Boosting underrepresented data within a dataset to avoid biases when training ML/AI models or conducting data science projects.
3. Sanitizing data to make it usable while maintaining privacy and security.

By addressing these challenges, Gretel empowers organizations to unlock the full potential of their data and drive innovation more efficiently.