For AI teams
The platform layer you would otherwise build.
Routing, fallback, observability and shared context, so your team works on the model rather than the plumbing.
What the central team inherits
- Every department asking for a different model
- Quality regressions discovered by users, not by you
- No shared way to evaluate one model against another
- Agents built in isolation, each with its own idea of context
What changes
- Routing as a policyDecide which request goes to which model by cost, latency or capability, and change it without a deploy.
- Evaluation on real trafficCompare models on production requests, with the numbers that actually drive the decision.
- Shared context for every agentORVYX Brain gives agents the same grounded company knowledge, instead of each one starting blind.
- One place to answer the CFOSpend is attributed per team and per use case, so the conversation is about trade-offs, not totals.
Build on a layer, not on glue.
Bring your model estate, and we will map it onto the gateway.