Creating powerful partnerships through collaborative computation

Seclūd is a group of services on Azure that enable partnership between disparate organizations to harness the benefits of shared encrypted data—without compromising any party’s privacy.

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Maintain privacy
while sharing data

Seclūd's state-of-the-art cryptography and technology free you of privacy and liability concerns, allowing data-sharing partnerships where trust was not previously possible.

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Unblock data-partnering

Tap into $50 billion worth of data-sharing opportunities and collaborate with partners for AI-related services, research, or market insights, while all data content remains encrypted.

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Create privacy-preserving
apps easily

Seclūd makes it easy for developers to create an entire ecosystem of privacy-preserving applications and services. No experience with secure-computation tools is necessary.

Our current services

Seclūd is an evolving technology: our team is constantly working to develop new services and functionality. These services are available right now.

Graphic describing the Private Data Retrieval service

Private data retrieval

Private data retrieval allows individuals or organizations to obtain limited information about the content of data without revealing the data.

For example, one use of this technology is to detect breached passwords. It is possible for a person to discover whether their password has been compromised without anyone else seeing it by comparing the encrypted password with a database of breached passwords. The password query and response are both encrypted under the user’s key.

Offer this ability as a service to your employees, customers, and clients to demonstrate your commitment to their privacy and security.

Graphic describing the Private Prediction service

Private prediction

Through a trained machine learning model, Seclūd’s Private Prediction service enables inferencing on encrypted data without revealing the content of the data to anyone.

Private prediction comprises two related services: prediction on homomorphically encrypted data and prediction using multi-party computation.

This technology enables collaborative prediction by using partners’ datasets without the need for data sharing, even when partners are competitors or don’t share a basis of trust. Through it, we may begin to see advances in AI image reading and diagnostics in healthcare, manufacturing, and other industries.

Planned future services

Here’s a peek under the hood at some of the functionality we’re currently developing. If you don’t see what you’re looking for, please contact us. We’re always open to new ideas.

Compare two or more sets of data to find commonalities without the possibility of any party viewing any other party's data. Retailers, for example, could compare customer lists with partner businesses for co-marketing efforts targeting customers of both companies, without betraying the privacy policies of either organization. Compatible or competing organizations could compare supply-chain and product availability data to provide better service to their customers, without revealing sensitive information.

Aggregating data from multiple sources allows us to draw conclusions and derive insights much stronger and more powerful than is possible with just one set of data, but there are numerous issues with combining datasets from multiple sources. Organizations must consider regulatory issues, losing control over their data, and the fact that combining data makes it a more valuable target to hackers and thieves. Keeping the data encrypted throughout the entire process alleviates these problems.

For instance, using this service, healthcare institutions or insurance companies might combine their data in order to better understand patient health trends and tendencies, yet keep sensitive personal information private.

Previously, data sharing was impossible in privacy-sensitive industries such as finance, but with Seclūd’s encrypted computation services, it’s now a reality. The Collaborative Insights service allows organizations to glean important information without revealing sensitive data. For example, a financial institution could foil money-laundering schemes by sending an encrypted query to discover whether their potential clients have opened numerous accounts at other banks.

Graphic providing a general sense of Seclūd’s private computation services

See how Seclūd services can work in real life

This video shows some hypothetical use cases—take a look.

Seclūd technology

Homomorphic encryption and secure multi-party computation technologies protect private data during operations in Seclūd. Lattice-based homomorphic encryption is so secure that it’s believed to be unbreachable even by quantum computers.

Streamlined and easy-to-understand processes define Seclūd. Developers without any background in cryptography or security can easily add privacy layers to their applications and deploy any of Seclūd’s services. And, Seclūd’s simple APIs facilitate integrating its services into existing products. Our services are optimized for the best possible data privacy and highest performance.

Learn more about our technology
Seclūd technology