[maximeago]

The first link is the corporate website, it may not include all the product details you expected, sorry about that. You should get a lot more details on how it works if you try the tutorial and play with it yourself. This is at the bottom of the post, hopefully it satisfies your curiosity but happy to answer outstanding questions here of course.

[amitport]

Is this a productized Duet[1]? Are you using it under the hood?

(As far as I'm concerned, if the answer is yes to both, this has much potential. I'm just trying to figure out what I'm looking at)

Thank you!

[1]: https://blog.openmined.org/duet-demo-how-to-do-data-science-...

[maximeago]

Yes, there are many parallels with Duets we can look at Sarus as a productized version of it.

There are some differences though: - we designed for the trusted curator model where Duet is mostly for federated learning tasks in mind - the privacy policies are based on principles (such as: "DP-outputs with epsilon < 2 can be shared", "DP-synthetic data can be shared", or "weights of ML models can be shared"), then the gateway applies the principles to any query, whether it is a SQL query, an ML model or else. In Duet, it's all about manual validation of given queries.