Portkey

Portkey

Portkey is a reliability layer for production AI applications, designed to make calls to large language models as dependable as the rest of an engineering team's infrastructure. Through its AI Gateway, Portkey provides the caching, fallbacks, routing, and retries that turn a fragile dependency on an external model provider into a robust, production-grade connection. For teams whose applications have to stay up when a provider has an outage or a prompt suddenly costs more than expected, that reliability is the core value.

Caching is the most immediately measurable feature: identical calls return cached results instead of re-hitting paid endpoints, which customers report saves thousands of dollars, particularly across test suites that run the same prompts repeatedly. Fallbacks and routing take over when a primary provider degrades, redirecting traffic to a healthy alternative without the application noticing. Retries smooth over transient errors, and the gateway exposes more than 1,600 models through one unified API, so adding a new fallback provider is a configuration change rather than an integration project.

Because Portkey is open source and already powers more than 3,000 GenAI teams processing trillions of tokens daily, its reliability features are proven at scale rather than theoretical. The platform pairs them with real-time observability that monitors LLM behavior and catches anomalies early, so teams can see the effect of caching and routing decisions in their dashboards. It integrates with Microsoft Azure, MongoDB, GitHub, Docker, and Auth0, fitting into existing stacks. For any team that has felt the sting of an AI outage in production, Portkey supplies the operational primitives — caching, fallbacks, retries, and visibility — that make generative AI safe to depend on.