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Plain-language AI glossary

Term 32InfrastructureMeaning / context / connections

Infrastructure / Definition

API Gateway

A server that acts as a single entry point for AI API requests, handling routing, rate limiting, authentication, and load balancing across multiple AI providers.

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01

MeaningThe one-sentence definition.

02

ContextHow the idea works in practice.

03

UsesWhere the concept becomes useful.

01 / Plain-language context

How API Gateway works.

An API gateway sits between your application and AI providers (OpenAI, Anthropic, Google). It provides a unified interface so your app code does not need to handle provider-specific details. Gateways like LiteLLM, Portkey, and Helicone let you switch between providers, implement fallbacks (if OpenAI is down, route to Claude), and track costs across all providers in one dashboard.

Key capabilities of AI API gateways: (1) Provider abstraction: same API format regardless of which model you call, (2) Fallback chains: automatic retry with a different provider on failure, (3) Cost tracking: monitor spend across all providers, (4) Rate limit management: queue requests to stay within provider limits, (5) Caching: cache identical requests to reduce costs.

For production apps, a gateway becomes valuable when you use multiple AI providers or need reliability guarantees. Start without one (direct API calls are simpler), and add a gateway when you need provider fallbacks, cost monitoring, or multi-model routing.

02 / Practical uses

Where it helps.

  1. 01Multi-provider AI routing
  2. 02Cost tracking and budgeting
  3. 03Automatic failover between providers
  4. 04Rate limit management
  5. 05Request caching and logging
03 / Keep exploring
InferenceThe process of running a trained AI model to generate predictions or outputs from new inputs, as opposed to training the model.LatencyThe time delay between sending a request to an AI model and receiving the response, critical for real-time user-facing applications.Token Limits / Rate LimitingRestrictions imposed by AI API providers on the number of tokens processed or requests made within a given time period.Model ServingThe infrastructure and process of hosting a trained AI model and exposing it as an API endpoint for real-time or batch inference.