OpenPCC is an open-source framework aimed at ensuring privacy in AI inference. It draws inspiration from Apple's Private Cloud Compute while offering a fully open and auditable solution that users can deploy on their own infrastructure. The framework allows users to run AI models without revealing prompts, outputs, or logs, utilizing encrypted streaming, hardware attestation, and unlinkable requests to maintain privacy. Confident Security is developing a managed service called CONFSEC built on the OpenPCC standard. The repository includes a Go client and a C library that forms the basis for Python and JavaScript clients, along with various in-memory services for testing. OpenPCC implements Oblivious HTTP (OHTTP) to prevent compute providers from tracking user actions. Users are encouraged to set up an OHTTP Gateway and connect through an OHTTP Relay, with Oblivious.network recommended for immediate use. The article provides practical coding examples for developers, illustrating how to connect to a production service using OpenPCC. It includes details on configurations like identity policies and API settings, essential for creating client requests. For development, users can run commands using the Mage tool to execute tests and manage services efficiently. The code snippets demonstrate how to format inference requests and handle responses, emphasizing the technical implementation of the framework.