What Is an LLM Gateway? How It Works and How to Choose One

An LLM gateway is presented as a centralized layer between enterprise applications and AI models that standardizes access, authenticates requests, applies policies, routes workloads among hosted and open-weight models, manages costs, and logs usage and performance. The text highlights security risks at this layer, citing the March 2026 compromise of malicious LiteLLM packages on PyPI that allegedly harvested cloud credentials and API keys, and argues that gateways require strong supply-chain security, private processing environments, and verifiable controls. It describes a typical request flow in which an application sends a request to one endpoint, the gateway validates access and budget rules, selects or fails over to an appropriate model, and checks and records the response. Key selection considerations include self-hosted deployment options, vendor security practices, open-weight model support, and compliance-ready audit logging. Prem AI promotes its Enclave API as a private, OpenAI-compatible gateway that uses encryption, hardware-isolated enclaves, zero data retention, and cryptographic attestation to process supported open-model requests while limiting external access to sensitive data.

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