One Loop, Two Speeds
When a workflow arrives, the orchestrator uses skill profiles to assign each step to its best-fit model, then runs it. In the background it keeps watching, probing periodically and updating profiles as it learns, swapping a model when drift is real or a clearly better one shows up. One loop at two speeds: the evidence that catches drift sharpens every future decision.
Why OpenMesh
Better outcomes — 15 - 31 pp headroom
Higher Efficiency — 3 - 5x throughput
Lower cost — up to 97% lower
Built for a world where agents run agents
AI workflows are now long chains of small steps, some easy, some hard. Routing every one to a single frontier model means you overpay, you wait, and you can't see when quality slips. OpenMesh runs the workflow like a team, assigning each step to the model best suited for its skill, then watching as it runs, swapping models that drift, and getting sharper with every run.