Rate Limiting

Rate Limiting controls how many requests a client can make to an API in a given time window — protecting infrastructure from abuse, ensuring fair access among customers, and enforcing pricing tiers. Every major AI API enforces rate limits in multiple dimensions: requests per minute (RPM), tokens per minute (TPM), tokens per day, and sometimes concurrent connections. Rate limits scale with usage tier — paid customers, higher tiers, and enterprise contracts get higher limits than free or starter tiers. OpenAI publishes tier-based limits (Tier 1 through Tier 5), Anthropic uses similar tiered approaches, and other providers follow comparable patterns. Hitting rate limits in production causes 429 HTTP errors that applications must handle gracefully — typically through exponential backoff retries, request queuing, or load balancing across multiple API keys and providers. Tools like the various LLM gateway products (LangChain, Helicone, OpenRouter, Portkey) help abstract rate-limit handling. AI governance, AI compliance, and AI risk management programs include rate-limit handling in resilience reviews supporting responsible AI through reliable enterprise AI operations.

Centralpoint Routes Around Rate Limits: Oxcyon's Centralpoint AI Governance Platform fails over between providers when rate limits trigger — OpenAI, Gemini, Claude, Llama, and embedded models. Centralpoint meters consumption, keeps prompts and skills on-prem, and embeds resilient chatbots into your portals via a single JavaScript line.


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