Platform
One delivery protocol around many agent workers.
Orcho is the stable layer around agent work: typed plans, phase gates, review loops, handoff decisions, evidence and run history. Start here when you want the product model before going into docs.
Agent work needs a production harness.
AI agents can write, inspect and repair software. What teams still lack is a production harness and control plane for deciding what counts as delivered. Orcho names that missing layer: typed plans, review contracts, readiness gates, event timelines and evidence bundles that survive the worker session.
/platform/agent-delivery-protocol/Not every task deserves the same workflow depth.
Control depth is the operator choice between speed and evidence. Orcho exposes fast, team and governed postures so low-risk work can stay light while cross-system or high-risk work gets gates, handoff and final acceptance.
/platform/control-depth/Your agents will change. Your delivery protocol should not.
Teams already mix Claude, Codex, Gemini, Cursor, Cline and internal scripts. Orcho treats workers as replaceable participants under one delivery record, so changing a worker does not erase plan history, gates or evidence.
/platform/workflow-portability/Top-model intelligence belongs where it matters most.
AI coding spend grows when every phase uses the same expensive worker. Orcho makes runtime choice explicit: plan with strong reasoning, route bounded implementation and repair through cost-efficient compatible workers, keep review independent, and inspect the result by phase.
/platform/runtime-economics/Review should control the run.
Orcho puts gates and human handoff inside the delivery flow. A rejection requests retry feedback, routes to repair or halts the run — and the decision itself becomes part of the run history.
/platform/evidence-and-governance/