Product Update: Data Clean Rooms v2.0 now available on the Decentriq platform

An update from our product team – David Sturzenegger, Head of Product, Decentriq

We’re immensely proud to launch V2 of our data clean rooms. We introduce Python support as well as numerous client-requested features.

Decentriq users can look forward to more types of computations, smoother workflows and an array of UI updates that will together make it easier than ever before to unlock new value from your sensitive data. All this is based on your valuable feedback.

Now let’s look at this in greater detail!

1. Python and machine learning

Decentriq’s data clean rooms can now support arbitrary Python in while guaranteeing the same high level of security. You can securely run any Python script in confidential computing through our platform’s UI without the need to modify your existing code. This opens a whole new universe of potential applications as machine learning algorithms are now supported out of the box. For the first time, our users can train and deploy machine learning algorithms on sensitive data that is never revealed to anyone.

2. More confidential computing capabilities

We have been working to support Python in our data clean rooms for a while, and this is now a reality thanks to our modular driver/workers architecture. With this new architecture, our data clean rooms are now confidential computing technology agnostic.

Our data clean rooms use Intel SGX to operate a driver enclave that coordinates different workers which can also run on other confidential computing technologies. This lets us accommodate every client’s needs in terms of compute type and data locality as well as easily integrate new confidential computing technologies such as AMD SEV/SNP or the upcoming Intel TDX.

3. Brand new SDK

We are proud that our data clean room UI can already accommodate many types of end-user applications and use-cases. But we are equally thrilled that some of our clients wanted to build their own applications based on Decentriq’s platform to automate their data collaborations.

To enable this, we just released a revamped version of our Python SDK which adds many convenience features and makes it even easier to work with our data clean rooms. Check out the Python SDK Quick Start tutorial or our Documentation page to learn more.

Are you as excited as we are for this latest version of Decentriq’s data clean rooms? If you would like to learn more about these updates, let us know and we’ll be more than happy to walk you through.

We’re always looking for ways to improve our data clean rooms to make it even easier for you to unlock new value from sensitive data assets.

David Sturzenegger
Head of Product
Decentriq