Confident Security provides a verifiably-private inference API that enables developers to build AI-powered products while maintaining data privacy, security, and regulatory compliance. The company's core offering is an OpenAI-compatible API and SDK that routes AI inference requests through a privacy-preserving architecture based on OpenPCC, an open-source standard the company developed in alignment with Apple's Private Cloud Compute (PCC) design principles. The platform is built on confidential computing technology, which ensures that prompts, responses, and user data are processed in a stateless, anonymized manner. Key architectural properties include: - Zero logging of prompts or responses - No use of interaction data for AI model training - No transmission of data to third parties - Complete anonymization of requests - Tamper-proof, remotely verifiable computation - No privileged operator access to private computation Confident Security supports a range of leading large language models (LLMs), including Mistral, Gemma, Llama, Phi, Qwen, and Deepseek, among others. It also allows enterprises to host, manage, and distribute custom models under the same privacy and security guarantees. The platform is designed to help organizations meet regulatory compliance requirements, including GDPR, CCPA, and HIPAA, positioning itself as an alternative to traditional self-hosting solutions, which the company argues are insufficient for achieving verifiable data privacy. Confident Security is a member of the NVIDIA Inception Program, the Cloud Security Alliance, the Confidential Computing Consortium, CyLab Venture Network, and South Park Commons. The company takes explicit financial responsibility for any breach or misuse of data processed through its platform.