AI Gateway Integration

ai gateways are becoming the standard control point for operating ai systems at scale they provide a unified place to route requests, standardize formats, apply access controls, and capture detailed metadata about how models are used when connected to amberflo, your ai gateway becomes significantly more powerful amberflo transforms raw gateway traffic into fully structured, attributed, and actionable usage data this enables real time ai governance, cost attribution, budget enforcement, and unified reporting across all your ai workloads amberflo does not provide its own ai gateway instead, amberflo integrates with third party gateways, allowing you to use whichever gateway fits your stack i’m ready to jump in choose the option that applies to you ➡️ i already have an ai gateway running connect your existing gateway to amberflo using our integration guide quickstart connect an existing ai gateway ➡️ i need an ai gateway to get started deploy an ai gateway and integrate it with amberflo quickstart deploy an ai gateway and connect it to amberflo i want to learn more before i start understanding how ai gateways and amberflo work together helps clarify why this integration is so valuable why ai gateways matter modern ai workloads are complex, branching, and heterogeneous a single user request may involve multiple models, tools, agents, retries, or external apis ai gateways solve the operational challenges by providing a single entry point for all model traffic consistent request and response formats centralized routing and authentication detailed request logging and metadata capture rate limiting, retries, model switching, and fallback behavior a clean abstraction over multiple ai providers and model types this creates the visibility and control point needed for accurate governance and measurement why ai gateways + amberflo are a powerful combination amberflo extends your gateway with real time intelligence rich metering tokens, model calls, latency, retries, error paths, and tool invocations attribution map usage to teams, applications, environments, or business units cost calculation apply public prices or custom internal rates budget enforcement protect against runaway usage real time guardrails instantly alert or block conditions that exceed policy unified visibility combine ai gateway traffic with cloud spend, on prem usage, or custom metered data chargebacks and reporting generate granular cost insights and internal billing together, this forms a complete system for ai governance and control use cases unlocked by this integration multi tenant attribution for shared ai infrastructure real time cost monitoring and budget protection comparing and evaluating models across vendors tracking tool and agent usage understanding cost per workflow, task, or user interaction consolidating ai usage data across multiple gateways or providers generating internal chargebacks or customer billing based on actual usage next steps start with one of the quickstart guides above