What does an AI gateway add beyond direct provider SDK calls?
An AI gateway centralizes routing, provider credentials, retries, usage metering, and observability so teams can control production behavior consistently.
ai gateway
AI Gateway: Routing, Observability and Budgets
Use an AI gateway to route requests, manage provider integrations, monitor usage, and apply budget controls with observability built in.
Built for teams comparing observability, cost control, and provider operations workflows before rolling out production AI features.
What to measure
| Metric | Why it matters |
|---|---|
| Provider routing outcomes | Track where traffic goes and why fallback rules trigger. |
| Latency + error rate by provider | Detect instability before it becomes cost or UX debt. |
| Usage and cost by route/project | Measure whether routing actually saves money. |
| Retries and failovers | Monitor hidden spend multipliers in gateway policies. |
Proof from the product
Real UI snapshot from AI Cost Board used in production workflows.
Provider-level drilldown for spend and token economics.
When to choose this workflow
- • Teams routing traffic across OpenAI, Anthropic, Gemini, or Azure OpenAI.
- • Platform teams enforcing budget limits and provider policies centrally.
- • Engineering teams needing a base-URL integration path with unified monitoring.
Feature pages to review
Comparison pages
Vercel AI Gateway vs AI Cost Board
Compare Vercel AI Gateway and AI Cost Board for unified AI API access, observability, and cost governance workflows.
Cloudflare AI Gateway vs AI Cost Board
Compare Cloudflare AI Gateway and AI Cost Board for gateway controls, observability, and AI cost governance workflows.
OpenRouter vs AI Cost Board
Compare OpenRouter and AI Cost Board for unified model access, routing visibility, and cost governance workflows.
Use-case pages
RAG Cost Monitoring
Track retrieval + generation cost, latency, retries, and error patterns for RAG pipelines in production.
Agency LLM Monitoring by Workspace
Monitor LLM cost, usage, and incidents per client workspace for agencies managing multiple AI deployments.
FinOps for AI API Costs
Apply FinOps discipline to AI API spend with team allocation, variance analysis, forecasts, and governance workflows.
Track real AI API operations with AI Cost Board
Monitor cost, usage, latency, errors, request logs, and provider performance in one operational dashboard.
FAQ
Is AI Cost Board an AI gateway or an observability layer?
AI Cost Board supports gateway-style provider integration workflows and focuses on observability, cost control, and governance for production operations.
Which gateway metrics should I track first?
Start with provider-level latency, errors, retries, cost per route, and traffic distribution across projects and environments.