Use Cases

The Nillion Network enables a variety of use cases in which sensitive data is leveraged and processed while remaining protected using cryptographic techniques.

Secure Storage and Retrieval

With Private Storage, users can store and retrieve secrets on the Nillion Network via a RESTful API. It is up to the developer which privacy-enhancing technology (PET) they want to use and on which node or cluster of nodes they want to rely. Querying and secure computation of these secrets is available for large scale database operations. Homomorphic encryption offers data protection and supports computation over data even if only one node is being used. Secure multi-party computation makes it possible to go one step further, making it possible to store in a decentralized way while relying on the strongest form of encryption possible (i.e., information-theoretic security).

Private Inference

Private LLMs can be incorporated into any application via a RESTful API. These are compatible with OpenAI standards and any AI-powered application can be built. Common sectors from which developers build apps that require private inference through the prompts and answers include (but are not limited to) health and finance.

Retrieval-Augmented Generation (RAG)

Combining retrieval-augmented generation (RAG) with PETs makes it possible to leverage the powerful features of contemporary AI solutions while storing data in an encrypted form at all times. This can unlock new use cases by reducing the amount of data that must be decrypted to accomplish a given task.