Data is both a valuable asset but also a big reputational risk for companies. Accessing and utilizing data is the building block of the Machine Learning revolution but it is still gated behind inefficient processes that add complexity and increase the data leakage risk. Currently there is almost no way to access and utilize the world’s most sensitive and valuable data, but we are changing this. With Confidential Machine Learning we allow you to develop and deploy entirely new models based on data you never actually see.
Powered by Confidential Computing we employ the latest advancements in cloud computing and cryptography to ensure a new way to interact with data. Our technology ensures that data is protected at all stages of the data science workflow from keeping it safe at rest, at transit and even during computation.
We make the access to previously unattainable data an effortless process. Worrying about data confidentiality is a thing of the past, with the decentriq platform training new Machine Learning models on unseen and sensitive data is as easy as never before.
With confidential Machine Learning, giving access to external data science teams has never been easier, collaborate fast and in an agile way without the cumbersome process of physical on-premise presence and complex legal contracts.
Train Machine Learning models on data you never see.Complete confidentiality with familiar APIs
E.g. Microsoft Azure Confidential Computing Instance
Ensure ownership and control over the data.Absolute confidentiality with retraction option at any time
decentriq's Confidential Machine Learning Inference module allows doing machine learning prediction and inference in a privacy-preserving and secure way. When performing prediction using our platform, the data and the model are provably kept confidential from all parties, including decentriq and any hardware infrastructure provider.
decentriq's Confidential Machine Learning Inference integrates seamlessly into workflows without compromising speed and scalability. This opens up fundamentally new ways for model owners to utilize and monetize their models while protecting intellectual property of their models and data privacy of their users.
Confidential Machine Learning Inference keeps provable confidential any data fed to any model, unlocking the possibility to take advantage of easy cloud deployment even in the most privacy-strict environments.
Scalable ML model cloud deployment, while having full IP protection
Deployed in the Cloud
Secure data sharing, while having full control over what happens with the data