2 docs tagged with "failover"

Running AI workers costs money — every token processed incurs a charge. WRM's cost management features give you control over spending through budgets, visibility through cost tracking, and resilience through provider failover.

When a worker is dispatched, the platform needs to decide two things: which model to call, and which CLI or runtime to run the agent in. The first decision comes from the worker's model preferences. The second — which execution harness to use — is derived from the first. This page explains how these concepts relate and how the platform resolves them.