Observe and control AI applications with caching, rate limiting, and analytics for any LLM provider.
A control layer for your AI applications — add caching, rate limiting, and cost tracking to any AI provider.
Cloudflare AI Gateway serves as an intelligent proxy layer between AI applications and model providers, offering comprehensive observability, control, and optimization features for AI workflows. It acts as a universal interface that can route requests to any major LLM provider while adding enterprise-grade management capabilities without requiring application code changes.
The core value proposition is operational control over AI applications in production. AI Gateway provides detailed analytics on request volumes, token consumption, costs, and performance across all model providers. This visibility is crucial for organizations running AI applications at scale who need to understand usage patterns, optimize costs, and ensure reliability.
Key features include intelligent caching (serving repeated requests from cache for speed and cost savings), rate limiting (controlling application scaling and preventing runaway costs), request retry and model fallback (improving reliability through automatic failover), and cost tracking across multiple providers. The caching system is particularly powerful for AI agents that make repetitive queries or serve similar user requests.
For AI agent deployments, Gateway enables sophisticated traffic management patterns like A/B testing between models, gradual rollouts of new model versions, and automatic fallback to backup providers during outages. The observability features help identify performance bottlenecks, track agent behavior patterns, and optimize prompt engineering based on actual usage data.
Integration requires only changing the API endpoint URL while keeping existing authentication and request formatting. This makes it easy to add Gateway to existing applications without code rewrites. The service supports all major providers including OpenAI, Anthropic, Google, Replicate, and Workers AI, with a unified interface for multi-provider applications.
AI Gateway integrates seamlessly with Cloudflare's broader AI ecosystem including Workers AI for inference and Vectorize for vector storage. This creates comprehensive AI application infrastructure running entirely on Cloudflare's edge network. The service is available on all Cloudflare plans including free accounts, with usage-based pricing for advanced features.
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Cloudflare AI Gateway provides essential observability and control for production AI applications. The combination of caching, rate limiting, and analytics makes it valuable for any organization running AI at scale.
Single interface to route requests across 20+ AI providers including OpenAI, Anthropic, Google, and Replicate while maintaining provider-specific authentication and formatting.
Use Case:
Building AI applications that can switch between providers for cost optimization, feature availability, or reliability without changing application code.
Automatic caching of API responses with configurable TTL and cache keys, serving repeated requests directly from Cloudflare's edge cache for sub-10ms response times.
Use Case:
AI agents serving similar user queries can dramatically reduce latency and API costs by caching common responses, especially for FAQ-style interactions.
Granular rate limiting by user, API key, model, or custom parameters with configurable time windows and quota policies to prevent cost overruns and ensure fair usage.
Use Case:
Multi-tenant AI applications needing to control per-user API consumption or prevent single users from consuming entire model quotas.
Automatic retry logic with exponential backoff and intelligent model fallback, routing failed requests to backup providers or alternative models seamlessly.
Use Case:
Production AI agents requiring high availability can automatically failover to backup providers during outages or rate limit situations.
Detailed visibility into request patterns, token usage, costs, latency, error rates, and model performance across all providers with real-time dashboards and historical trends.
Use Case:
Organizations running AI applications at scale need detailed observability to optimize costs, identify bottlenecks, and understand user behavior patterns.
Sophisticated traffic routing for testing different models, prompts, or providers with percentage-based splits and gradual rollout capabilities.
Use Case:
AI product teams can safely test new models or prompt variations against baseline performance without affecting all users simultaneously.
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View Pricing Options →Multi-provider AI applications needing unified observability and control
AI agents requiring high availability through automatic provider failover
Cost optimization for AI applications through intelligent caching and rate limiting
Production AI services requiring detailed analytics and usage monitoring
Cloudflare AI Gateway works with these platforms and services:
We believe in transparent reviews. Here's what Cloudflare AI Gateway doesn't handle well:
AI Gateway adds minimal overhead (typically <10ms) as it runs on Cloudflare's global edge network. For cached responses, latency can actually improve dramatically with sub-10ms response times. The global deployment ensures the proxy layer is close to both your application and the target AI provider.
Yes, integration requires only changing your API endpoint URL from the provider's direct endpoint to your AI Gateway endpoint. All existing authentication, request formatting, and response handling remain unchanged, making adoption seamless for existing applications.
AI Gateway caches responses based on request content and parameters. For deterministic models with identical inputs, caching provides exact response reuse. For non-deterministic responses, you can configure caching policies based on your application's tolerance for response variation versus performance gains.
AI Gateway provides comprehensive analytics including request volumes, token consumption, costs per provider, response latency, error rates, and usage patterns. Real-time dashboards show current activity while historical reports help with cost optimization and capacity planning.
Weekly insights on the latest AI tools, features, and trends delivered to your inbox.
Enhanced A/B testing capabilities for model comparison, improved caching algorithms with semantic understanding, expanded provider support including latest AI services, and advanced cost optimization recommendations based on usage patterns.
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