Users who we can work with and provide them with the knowledge of how Differential Privacy can help with their data, and how it can help them share their data in a privacy preserving manner, helping them find utility to their data in a safe and GDPR compliant manner.

The project is at a functional prototype stage, with core components tested on synthetic data. Software supports configurable model training and privacy parameter adjustment, providing a flexible foundation for privacy-aware machine learning workflows.

Next steps include:

1. Validation across additional use cases
2. Refine integration points for external systems
3. Engage with partners for them to use software

The code can be made available on request, for people to run experiments using datasets that have been used during its development.