AI Gateway
Middleware layer between applications and AI model APIs for routing, monitoring, rate limiting, and caching.
AI Gateway is middleware between apps and LLM APIs – for routing, caching, monitoring, and cost control.
Explanation
AI Gateways abstract multi-provider complexity: unified request format, automatic failover on errors, response caching for repeated queries. Examples: Portkey, LiteLLM, Cloudflare AI Gateway. Provide observability: token tracking, latency metrics, cost management.
Marketing Relevance
Essential for enterprise AI: governance, cost control, reliability. Enables secure AI usage in organizations.
Example
Corporate gateway routes all AI requests: sensitive data to Azure OpenAI, rest to cheaper providers.
Common Pitfalls
Additional point of failure. Configuration complexity. Cache invalidation with dynamic responses.
Origin & History
Emerged 2023 as response to multi-provider complexity. Cloudflare AI Gateway, Portkey, and LiteLLM are leading solutions for enterprise AI management.
Comparisons & Differences
AI Gateway vs. OpenRouter
AI Gateway is self-hosted or enterprise-managed; OpenRouter is hosted API aggregator with own billing.
AI Gateway vs. Direkte API-Nutzung
AI Gateway provides caching, fallback, and monitoring; direct APIs require separate implementation per feature.