Ask HN: Event analytics without collecting personal data

Hi HN! I'm a solo founder building privacy-enhancing software solutions. I'm currently working on a new product that aims to make event analytics (e.g. for mobile apps, software or IoT devices) more privacy-friendly. I started working on this because I find that current event analytics solutions (e.g. Mixpanel, Firebase or Heap Analytics) are not very privacy-friendly as they collect and centralize large amounts of personally identifiable data.

With my product, Konsens, I want to pursue a radically different approach: Instead of centralizing the event data, Konsens keeps it on the client device and analyzes it there to answer complex questions about user behavior (e.g. how many users use features X & Y together). Only the de-identified answers of these questions are then sent to the backend, where we use a differentially private aggregation mechanism to combine them with data from other users and form anonymous result sets. That way, no personal data ever leaves the device, which is a big win for privacy. The two techniques (differential privacy & federated computing) are not new and companies like Google or Apple already employ them with great success, they haven't reached the mainstream yet though and are rarely used in event analytics. I want to change that.

After working on this for six months I have an initial prototype that I'd like to test with the first users in a closed beta (I currently have client libraries for iOS & web). If you're interested please have a look at the website to learn more and sign up for it: https://konsens.app

Feedback and comments are highly appreciated in any case!