Confidential computing is a security model that protects data while it is being processed, not just when it is stored or sent over a network. It uses hardware-based trust, such as a Trusted Execution Environment or secure enclave, to isolate code and memory from the rest of the system, including cloud operators and privileged software.
This matters because many attacks target the processing layer: an administrator account, a compromised hypervisor, a malicious insider, or exposed telemetry can reveal sensitive prompts, keys, or business data. In defense, confidential computing can narrow who can inspect live data and add cryptographic attestation so a client can verify that trusted code is running inside genuine protected hardware. In AI services, it is often used to support private chat modes and reduce backend visibility, but it does not protect against endpoint compromise, weak retention practices, or flawed enclave implementations.