AI gateway & observability
One endpoint in front of every provider — with budgets, keys and traces you own.
An AI gateway is a proxy that presents one OpenAI-compatible endpoint and routes to whichever provider you configure, adding virtual keys, per-key budgets, fallbacks and a spend log. Paired with a tracing tool such as Langfuse it also answers what a request actually did, and what it cost.
Every company that uses more than one model provider arrives at the same three problems: keys are pasted into too many places, nobody can attribute spend to a feature, and when a provider degrades, everything downstream degrades with it. A gateway solves all three without touching application code — the base URL stays the same while the routing behind it changes.
The observability half matters just as much once agents are involved. A single user request can become forty model calls, and without traces the only debugging tool is a guess. Langfuse records the tree, the latencies and the cost per step; Opik adds scoring so a prompt change can be measured rather than argued about.
The applications in this stack
Three steps, no Docker knowledge required
Pick the app and the size
Choose memory and storage from the plan table. Every plan is a single-tenant instance with its own volume, its own configuration and its own admin account.
We deploy and harden it
TLS on your domain or ours, firewall, a version pinned to a reviewed release, nightly off-box backups and isolated secrets.
You log in and build
The admin account is yours. Add your API keys, invite your team, export your data whenever you want. Patching stays with us.
Straight answers
Does this replace my provider accounts?
Can I mix local and commercial models?
Is trace data private?
Is this a shared account or my own instance?
Do I have to know Docker?
What is included in the monthly price?
Can I move to a bigger plan later?
Put your AI stack on your own box
Pick an app, pick a size, and have it running today. Month to month, cancel whenever.