How Interfaze serves 50 million requests a month on Vercel
Interfaze’s stack shows one way to run checkable AI workloads: isolated code execution, provider failover, durable workflows, and version-specific deployments.
Interfaze serves **50 million requests a month** from a Vercel backend using Fluid compute. Its models return structured results with source locations and confidence scores, while Vercel Sandbox isolates model-written code.
For agent-backed products, separate deterministic extraction from general-purpose generation and make outputs inspectable. **AI Gateway** supplies provider failover and routing, while **Workflow SDK** preserves long-running email sequences across retries and pauses.
Interfaze serves **50 million requests a month** from a Vercel backend using Fluid compute. Its models return structured results with source locations and confidence scores, while Vercel Sandbox isolates model-written code. For agent-backed products, separate deterministic extraction from general-purpose generation and make outputs inspectable. **AI Gateway** supplies provider failover and routing, while **Workflow SDK** preserves long-running email sequences across retries and pauses. This is a vendor case study, not an independent performance comparison. Provider quality still varies even for nominally identical open models, and hosting model weights on GPUs remains slower than the roughly three-minute Vercel build described.
This case study combines several prior infrastructure controls in one production account: inspectable structured outputs, isolated execution for model-written code, gateway routing and failover, and durable workflows for paused or retried sequences. It supports the architecture pattern, but vendor-reported scale and build speed do not establish comparative performance, cost, or reliability.