Monks has generative AI in production across Anthropic, OpenAI, and ElevenLabs — and whatever model a brief calls for next. That multi-provider reality is powerful and hard to govern: cost, prompt and output logging, PII control, rate limits, and fallback all multiply with every model. Cloudflare AI Gateway sits in front of all of them — one pane for cost, caching, safety, and observability, with a one-line change to how you call each provider.
Multi-model is a margin and trust problem before it's a tech one. When AI is in production across three+ providers and thousands of people, the questions pile up fast: what did this client's AI usage actually cost? Is brand or customer data leaking into a model prompt? Which workflows are burning tokens on repeated calls that could be cached? Can you prove, per client, what was sent and returned? Answering those across providers — without a governance layer — means custom plumbing, rebuilt for every model and every team.
Point your existing Anthropic, OpenAI, and ElevenLabs calls through AI Gateway — no model change, no re-architecture. You get:
See exactly what each client, team, and model is spending — and cap it. Turn runaway token spend into a managed line item instead of a quarter-end surprise.
Repeated and near-identical calls — common across campaigns and templated workflows — served from cache instead of re-billed to the provider. Lower cost and lower latency on the same output.
Strip sensitive brand or customer data before it ever reaches a model provider, and enforce content guardrails — so AI in client work stays inside the lines you set.
Every request and response, logged and searchable across providers. Prove to any brand exactly what was sent and returned — the audit trail multi-model AI usually lacks.
If a provider errors or rate-limits, route to a backup automatically. One integration point in front of every model, so adding or swapping providers is config, not a rebuild.
Protect against runaway loops and abuse with per-key, per-model rate limits — the cost and stability guardrail under high-volume AI workflows.
Per-client cost visibility + caching turn runaway token spend into a managed line item.
PII redaction and full audit logs let Monks tell brands exactly how their data is handled across every model.
One control plane instead of bespoke plumbing rebuilt per model — more time on the creative and AI work.
Monks is as AI-forward as any services firm in the world — Anthropic, OpenAI, and ElevenLabs already in production. AI Gateway is the layer that makes all of it governable, auditable, and profitable at scale, with a one-line change to how you call each provider. Worth 30 minutes to map it to how Monks runs AI today?