# Private Inference for AI This chapter introduces Nesa's cutting-edge hybrid approach to security and privacy enhancement. The essence of this hybrid design lies in the thoughtful integration of hardware-based and cryptographic-based solutions, each selected and optimized for varying scenarios within our ecosystem. Our hybrid security and privacy is grounded in the recognition that privacy concerns manifest in different forms—users may wish to conceal their input data or the results of their inferences, while node owners might seek to protect the confidentiality of their model parameters. Our hybrid design acknowledges the unique requirements of these use cases by deploying the most appropriate privacy-preserving technologies. This chapter elucidates the rationale behind Nesa's hybrid strategy, offering a comprehensive blueprint for achieving the highest standards of security and privacy while maintaining the usability and efficiency of the decentralized inference process. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.nesa.ai/nesa/major-innovations/private-inference-for-ai.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.