The inference control plane.
Explore the intelligence layer between an application and a model endpoint: the request, the policy, the provider path and the resulting trace.
One intelligence layer
across your AI stack.
Bring applications, model endpoints and inference signals into one coherent view. This interactive architecture illustrates the platform concept—not a set of active provider connections.
Observe the request.
Connect latency, token usage and outcome with the workload that produced them.
Make the decision explicit.
Understand a routing choice in terms of policy, constraints and provider signals.
Retain the evidence.
Follow the request beyond a summary metric to its individual trace and context.
Make every boundary explicit.
- Application boundary
- An application creates the task and its constraints. The architecture illustrates agents, copilots, search, support and workflows as different request sources—not active customer deployments.
- Decision boundary
- A control plane can apply routing constraints before choosing an endpoint. The visible path selector is an interactive illustration, not a gateway making provider calls.
- Evidence boundary
- A useful record explains both the request and its outcome. The trace explorer demonstrates how to inspect that relationship with a fixed sample dataset.
Know what is available.
The platform shown here is an interactive frontend concept. Its architecture, providers and request paths are simulated. The separate benchmark workspace currently implements accounts, saved run records, comparisons and exports.
Use the workspace access page for that developer release, or contact engineering to discuss the wider platform direction.