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Learn how AI Gateway load balancing routes traffic across models, providers, regions, quotas, and fallback paths for reliable enterprise LLM applications.

Learn what to monitor in an AI Gateway, including token usage, cost, latency, provider health, fallback rate, audit logs, and tenant-level analytics.

Learn how AI Gateway rate limiting controls requests, tokens, providers, tenants, and cost budgets for enterprise LLM applications.

AISIX model ensembles fan one chat request to a panel of LLMs, then a judge synthesizes one answer — so several low-cost models can rival a frontier model.

Learn what an AI gateway is, how it works, and why enterprise teams use it to secure, govern, route, and observe LLM traffic.

Discover why structured APIs are 45x more cost-effective than raw LLM computer use and how API7/APISIX can manage them for AI consumption.

Learn how to manage diverse LLM ecosystems, optimize costs, and ensure high availability by load balancing multiple LLM backends with Apache APISIX.

Explore the core mechanics of Large Language Models (LLMs) and their crucial role for developers and API gateway users.

Discover how Large Language Models (LLMs) enhance API gateways with intelligent routing, automation, and analytics.