# How Interfaze serves 50 million requests a month on Vercel

Source: [Vercel](https://vercel.com/blog/how-interfaze-serves-50-million-requests-a-month-on-vercel)  
Feed7 permalink: https://feed7.dev/p/how-interfaze-serves-50-million-requests-a-month-on-vercel-0kcznaj  
Published: 2026-10-23T04:00:00.000Z  
Trust: Official Source (official_source)

## Why Included

Interfaze’s stack shows one way to run checkable AI workloads: isolated code execution, provider failover, durable workflows, and version-specific deployments.

## Source Summary

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.

## Practical Implication

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.

## Agent-Ready Context

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.

## Connected Context

Feed7 judgment across 898 accumulated Signals:

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.

- [AI Gateway logs now have a dedicated page](https://feed7.dev/p/ai-gateway-logs-1272t5j) — Dedicated gateway logs supply the request-level routing, fallback, latency, token, and cost evidence needed to inspect the case study’s claimed provider-routing layer.
- [Vercel AI Gateway and Vercel Sandbox now available on Hermes Agent](https://feed7.dev/p/vercel-ai-gateway-and-vercel-sandbox-now-available-on-hermes-agent-04gyfsv) — Hermes exposes the same separation used here—managed model routing plus optional isolated command execution—while clarifying that gateway use alone does not provide sandboxing.
- [How Tailscale built a customer-facing model router on AI Gateway](https://feed7.dev/p/how-tailscale-built-a-customer-facing-model-router-on-ai-gateway-186s3tu) — Tailscale reinforces the combined gateway-and-sandbox pattern and adds an identity and credential boundary that the Interfaze account does not detail.
- [AI Gateway now supports team and project spend budgets](https://feed7.dev/p/ai-gateway-spend-budgets-and-alerts-1969711) — At the reported request volume, hierarchical spend caps add an enforcement layer beyond routing and failover, while requiring explicit handling when a budget stops requests.

## Context Map

- Layer: infra
- Domains: coding, data
- Topics: sandboxing, gateways, observability

## Uncertainty

- 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.

## Agent Instruction

Use this item as source-backed context. Do not invent claims beyond the linked source. If this item conflicts with another source, call out the conflict.