The best model keeps changing
Over the past year, the model considered best for writing, summarising, or understanding images has changed several times. Prices have changed too. If every app calls a model provider directly, switching models means changing code in many places.
A gateway sits between your apps and model providers. Apps call one API, and the choice of model lives in the gateway. Changing models becomes a configuration change, not a new project.
One task, a different model
Not every task needs the most expensive model. Answering a complex customer question may need a large model, but sorting e-mail or extracting an invoice number can be handled by a much cheaper small model, or even a local one.
With routing in the gateway, each type of request goes to the model that fits best on quality, speed, and cost.
A gateway turns "which model do we use?" into "which model for this task?"
Provider outages will happen
Every model provider is sometimes slow or unreachable. If your customer service agent depends on a single provider, customers feel that outage immediately.
A gateway can keep a backup model ready for each task. When the primary model fails or is too slow, requests are rerouted automatically, and customers still get an answer.
Costs you can see
Without a gateway, AI costs often appear only on the monthly bill, with no way to tell which app or team used them. A gateway records every request: the model used, the number of tokens, and the cost.
- Separate API keys for each app, team, or client.
- Quotas and budget limits that stop runaway usage.
- Cost reports per model and per app, in rupiah.
Data that must stay in-house
Some data, such as ID numbers, health records, or internal documents, should not be sent raw to model providers abroad. A gateway can mask sensitive data before sending it, turn off log storage, or route certain requests to a self-hosted model.
When you do not need a gateway yet
If you are only trying one AI feature in one app, you may not need a gateway yet. It becomes useful once AI runs in more than one app, when costs start to matter, or when an AI agent serves customers and must not stop.
We built Otora AI Gateway for exactly that: one OpenAI-compatible API, routing, fallback, quotas, and cost tracking. Access is currently available to project clients and partners.
If you are weighing how to manage AI usage in your company, tell us which apps and models you already use. We will help you judge whether a gateway is really needed.