AI Gateway
Unified AI Gateway for intelligent routing, load balancing, and secure access to 50+ LLMs with enterprise SLAs and full observability.
AI Gateway is a single, secured API layer that routes every LLM request across 50+ models — picking the right one for cost, latency, or quality — so your applications aren't locked into one provider.
What Are the Key Benefits of AI Gateway?
- 30–50% cost reduction through intelligent model routing
- 99.99% uptime with automatic failover across models
- Unified API — one endpoint for all LLM providers
- Complete audit logging for compliance and debugging
- Real-time cost and performance dashboards
What Are AI Gateway's Core Capabilities?
Intelligent LLM Routing
Route requests to the optimal model based on cost, latency, quality, task type, and availability.
50+ Model Support
OpenAI GPT-4/o, Anthropic Claude 3/4, Google Gemini, Meta Llama, Mistral, Qwen, and custom models.
Enterprise Security
Prompt injection defense, PII masking, content filtering, rate limiting, and IP allowlisting.
Full Observability
Request/response logging, token usage analytics, latency tracking, cost attribution, and alerts.
How Does AI Gateway Work?
Click a step to see the details.
Point your applications at one AI Gateway endpoint instead of individual provider APIs.
Define routing rules by cost, latency, quality, or compliance requirements per use case.
The gateway selects the optimal model in real time and fails over automatically if one is unavailable.
Prompt injection defense, PII masking, and content filtering run on every request.
Full request/response logging, latency, and cost analytics in one dashboard.
Continuously rebalance routing as pricing, performance, or new models change.
What Results Can You Expect From AI Gateway?
AI Gateway — Frequently Asked Questions
AI Gateway detects the outage and automatically fails over to the next-best available model based on your routing policy, so applications keep working without manual intervention.
Yes. Routing policies are configured per use case — a customer-facing chatbot might prioritize latency, while a batch analysis job might prioritize cost, all through the same gateway.
Request and response metadata is logged for observability and audit purposes, with configurable retention and redaction. Full-content logging can be disabled or scoped per application depending on your data policies.
By routing each request to the cheapest model that meets your quality bar for that use case, avoiding overpaying for premium models on tasks that don't need them, and negotiating volume pricing across providers on your behalf.
Yes. Custom and fine-tuned models can be registered alongside major providers and included in your routing policies like any other model.
Minimal changes — applications call one gateway endpoint instead of individual provider SDKs. Most teams complete the swap in under a day per application.
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