Pay for what the task needs
Simple work runs on fast, low cost models. Hard work goes to stronger ones.
Each task goes to the lowest cost model that meets its quality bar. If that model is slow or down, work moves to the next one.
Fallback is automatic. The run keeps going and the switch is logged.
Simple work runs on fast, low cost models. Hard work goes to stronger ones.
When a provider has a problem, the task falls back to another approved model instead of failing.
The run trace shows which model handled each step and why it was picked.
Every task carries a quality bar. Auto routing compares the approved models and picks the lowest cost one that can meet it.
Fallback is automatic. The run keeps going and the switch is logged.
If the first choice is slow or unavailable, the task moves to the next approved model and the run carries on. The switch is recorded in the trace.
Routing only ever chooses from the models your policy allows for that team and agent, so cost savings never bypass governance.
Controls cost, quality, latency, privacy, and task complexity.
It carries the quality bar for the work.
Only the approved ones for that team and agent.
The lowest cost model that meets the bar.
Slow or down? The next model takes over.
The trace shows which model ran each step.
Identity, access, approvals, supervision, audit and policy apply to every agent and every run, whichever part of the workspace it happens in.
See governance and auditShort answers to what teams ask before they put this part of SoftworkerAI to work.
Contact us directlyIt looks at the approved models for that team and agent and picks the lowest cost one that meets the quality bar for the task.
The task falls back to the next approved model and the run continues. The switch is recorded in the run trace.
No. Routing only chooses from the models your policy allows.
No. Routing only picks models that meet the quality bar for the task. It saves cost on simple work, not on hard work.
The multiplayer workspace for humans and AI agents is how teams move beyond prompting and safely hand AI real work. It gives people one place to plan, approve, and oversee execution, so they can run work with AI agents they can govern and trust.