Portkey is an LLM gateway platform that adds reliability, observability, and control features on top of any AI API. At its core, Portkey routes requests to your configured AI providers (OpenAI, Anthropic, Azure OpenAI, Bedrock, Gemini, and 250+ others) and handles fallback logic, load balancing, retry policies, and semantic caching automatically. The platform includes a guardrails system for input and output filtering: you can block PII, profanity, or off-topic requests before they reach your model, or flag responses that don't meet quality criteria. Logging captures every transaction with full context including user IDs, custom metadata, and cost attribution, surfaced in a dashboard with filtering and analytics. Portkey offers a virtual keys system that manages API credentials centrally, so individual developers or microservices never touch raw API keys. The Node.js and Python SDKs wrap the OpenAI SDK, making migration typically a two-line change. It's widely used in production AI apps that need enterprise-grade reliability without building the infrastructure themselves.

What the community says

Portkey gets strong reviews from production AI teams for solving the reliability problem that developers encounter when building on top of unreliable LLM APIs. The fallback configuration and semantic caching are consistently cited as the features that pay for themselves quickly. Some developers find the configuration surface complex for simple use cases and prefer Helicone for basic logging. The guardrails feature is increasingly relevant to enterprise buyers dealing with content moderation requirements.

See alternatives to Portkey →