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decentriq - Confidential ML Inference

dq technologies AG
Keep data private while whilst deploying machine learning models
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decentriq - Confidential ML Inference

dq technologies AG

Keep data private while whilst deploying machine learning models

Deploy scalable machine learning models in the cloud without compromising on security, speed and scalability

One of the biggest challenges for tech teams within data-driven organizations is deploying ML models in the cloud without compromising data privacy and security. Typically, to carry out ML inference, both the model and the input data must be on the same computer. Existing methods are cumbersome, complex and largely inefficient; discouraging cloud deployment.


  • Data Leakage or IP Risk: On one hand, data owners have to give up control of their data in order to extract the complete value of the external ML models. On the other hand, model owners have to risk losing their IP by deploying their models locally with the data owner.
  • Limitations to ML Model: If the model is deployed locally on the user's premises it often causes friction due to missing local infrastructure.  There are also limitations in speed, scalability and flexibility due to constraints of the user’s infrastructure. 


Keep control of your data without compromising on speed and scalability

With our advanced technological capabilities and in-depth market understanding, we have developed a solution that enables organizations to safely access and analyse data without compromising on confidentiality or giving up control of the data. 


  • Confidentiality Guarantees: Data is always encrypted and hidden for Azure and decentriq. We minimize the possibility of data leakage and maximize IP protection while giving the same confidentiality guarantees as an on-premise deployment. 
  • Speed, Scalability and Flexibility: Through Python APIs or a web application, Confidential ML Inference can integrate seamlessly into existing workflows without any code change. We offer fully elastic resource planning which allows users to scale resources based on their needs.


If you want to learn more on how you can safely and effectively deploy ML models for your organisation CONTACT US to discuss your requirements.

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