What is an AI Gateway?
An AI gateway routes, caches, and governs LLM traffic across providers. It is the infrastructure layer between your application and every model it calls. One integration, 400+ models, zero provider lock-in.
How an AI gateway works
Your application sends requests to the gateway instead of directly to providers. The gateway handles the complexity.
Intelligent routing
Routes each request to the optimal model based on cost, latency, and capability. Simple queries go to budget models, complex reasoning goes to frontier models. Configurable per API key.
Response caching
Caches identical and semantically similar prompts. Cache hit rates of 30 to 60% are typical in production. Cached responses return in under 10ms with zero token cost.
Automatic failover
Detects provider failures within milliseconds and reroutes to backup providers. Configurable fallback chains with exponential backoff and jitter. Your users never see an outage.
Observability
Token usage, latency, cost per request, per user, per model, per team. Real-time dashboards. No separate observability tool needed.
Governance and RBAC
Role-based access, budget caps per team, model allowlists, prompt guardrails, audit logs. 5-layer policy hierarchy from organization down to individual API key.
Compliance
SOC2, GDPR (EU hosting in Frankfurt), HIPAA-eligible. Zero data retention routing for sensitive workloads. All traffic encrypted in transit and at rest.
AI gateway comparison (2026)
How Requesty compares to other AI gateways across key dimensions.
| Feature | Requesty | Others (avg) |
|---|---|---|
| Models supported | 400+ | 50-200 |
| Setup time | 2 minutes | Days to weeks |
| Smart routing | Built-in | Manual or none |
| Response caching | Automatic | Some, varies |
| Failover | Sub-100ms | Partial or manual |
| EU hosting | Frankfurt | Limited |
| Pricing | Pay as you go | Enterprise contracts |
| Free credits | $10 | None |
See detailed comparisons: vs Kong · vs Cloudflare · vs Portkey · vs LiteLLM · vs OpenRouter
Who uses an AI gateway
Any team building with LLMs. Here are the most common patterns.
AI-powered products
Route customer-facing AI features through one API. Failover keeps your product running when a provider goes down. Caching reduces latency and cost.
Internal AI tools
Give every team access to AI through managed API keys. Budget caps prevent overruns. RBAC controls who uses which models. Audit logs track everything.
AI agents and workflows
Agents that chain multiple model calls benefit from routing (pick the right model per step) and caching (repeated tool definitions hit cache).
Cost optimization
Route 50-70% of traffic to budget models without quality loss. Cache repeated prompts. Track spend per team, per project, per API key in real time.
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Start freeFrequently asked questions
What is an AI gateway?
An AI gateway is middleware that sits between your application and LLM providers (OpenAI, Anthropic, Google, etc). It routes requests to the optimal model, caches responses, handles failover when providers go down, enforces rate limits, and provides observability. Think of it as a smart reverse proxy built specifically for LLM traffic. You change one URL in your code and gain access to 400+ models through a single API.
What is the best AI gateway in 2026?
The best AI gateway depends on your needs. Requesty is best overall (400+ models, intelligent routing, caching, fully managed). Kong AI Gateway suits teams already using Kong for API management. LiteLLM is the best open-source self-hosted option. Cloudflare AI Gateway is best for edge-first architectures. Portkey is strong for enterprise prompt management. For most teams, a fully managed gateway like Requesty eliminates infrastructure overhead.
Do I need an AI gateway?
You need an AI gateway if you use more than one LLM provider, want to reduce costs through caching and routing, need uptime guarantees with automatic failover, or require governance (RBAC, budget caps, audit logs). A single provider with a hobby project does not need one. Any production application with reliability, cost, or compliance requirements benefits from a gateway.
How much does an AI gateway cost?
Requesty uses pay-as-you-go pricing with $10 free credits and no minimums. You pay a small markup on token costs (typically 1 to 5%) in exchange for routing, caching, failover, and observability. The caching savings alone (30 to 60% cache hit rates) typically exceed the gateway cost. Kong and Portkey charge enterprise subscription fees. LiteLLM is free but you pay for your own infrastructure.