Production AI integrations, explained
One endpoint in front of several model providers — routing rules you can change without a deploy, a fallback path that is part of the design, and cost measured per request. Built for the products we run ourselves.
Private beta — no self-serve sign-up, no published SLA. We say so here rather than after you have filled in a form.
1,405,091
requests in a week
through our own gateway, 09.09 to 15.09.2026
2.8 s
median answer
half are faster than this
26.3 s
nine in ten answers faster than
speech and image profiles included
0.16%
requests got no answer at all
another 10.31% was saved by the fallback path
Measured 16.09.2026 from our own gateway log in a week. One gateway, twelve task profiles together — from short checks to speech recognition and synthesis. The profiles differ, so the median and the tail differ by a lot.
Gateway is responding
checked at 20:16 UTCThe single endpoint in front of our products is accepting requests. The time of the check is next to the heading: this page does not poll the gateway in your browser and does not pretend that it does.
Try it here
POST /api/v1/probeYour text goes through the same gateway our products use. Which model answers is decided by a routing rule, not by this page.
Other ways to solve this
| Approach | Who it suits | What it costs you |
|---|---|---|
| Call each provider directly | One provider, one use case, and no plan to change either | The provider outage becomes your outage, and switching later means touching every call site you wrote |
| A routing library in your codebase | You want provider abstraction and are happy to own it | Routing rules ship with your app: changing a model means a deploy, and cost stays invisible until the invoice arrives |
| A commercial gateway product | Standard needs, budget for per-seat or per-token pricing, data allowed to transit a third party | You configure what the vendor anticipated; anything else waits for their roadmap |
| QueryPort | You need routing you can change without a deploy, a real fallback path, and cost measured per request | We are small and the gateway is in private beta: no self-serve sign-up, no public SLA yet, and access is granted case by case |
When we are the wrong choice
Being straight about the edges: in these cases another route is the better one.
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You want a self-serve API key right now
There is no public sign-up, and we are not pretending otherwise. Documentation, usage terms, rate limits and support are not at a level we would call a product yet.
What to do instead: Talk to us if the fit is close, or use a provider directly until we open up.
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You need a published SLA and enterprise procurement
We run this for our own products first. Uptime is real but not contractual, and we will not sign a number we cannot yet defend with a year of data.
What to do instead: Pick a vendor whose SLA is part of the product. That is a legitimate requirement, not a formality.
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Everything must stay inside your own network
The gateway talks to external providers. A fully local setup is different work: your own hardware, your own weights, your own operations.
What to do instead: Worth a separate conversation. Local models solve the data question and lose on quality and cost.
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You are looking for a model, not an integration
We do not train models. We route to them, and we care about what happens when routing goes wrong.
What to do instead: Go to the providers directly, then come back when the operational questions start.
Glossary
- Gateway
- A single endpoint between your code and several model providers. Your application talks to one address; which model answers is decided by a routing rule you can change without redeploying the application.
- Routing profile
- A named rule set per task type — text, OCR, vision, speech. Each profile has its own provider order, its own limits and its own cost per request.
- Fallback path
- What happens when the primary provider errors or goes quiet. Without one, a provider incident becomes your product incident, usually at peak hours.
- Token
- The unit providers bill in, counted across both your prompt and the answer. This is why the length of a system prompt is a line item, not a formatting detail.
- Time to first token
- Delay between the request and the start of the answer. For an interface it matters more than total time: an answer that has started reads as fast even when it finishes slower.
- Prompt injection
- Text arriving from a user or a document that carries instructions for the model and displaces yours. Mitigated by separating roles and validating what came back — not by trusting the model.