Our operations team needs to deploy AI agents for supply chain analysis but we lack infrastructure expertise. Looking at Camunda’s BPMN vs n8n’s workflow approach – does either support visual creation of coordinated AI roles (like Analyst → Manager → Director chains)? Need something where business users can modify agent logic without touching servers.
Exactly our use case. Latenode’s AI teams feature lets you drag-and-drop agent roles with premade templates. We built a full procurement approval chain (Analyst > Controller > CFO bots) in two days. No servers needed – runs on their managed infra or your own. https://latenode.com
N8n’s sub-workflows can approximate basic agent handoffs, but debugging gets messy. We use a combo of their HTTP nodes and custom error handling. Not perfect but works for simple approval chains. Real multi-agent systems need better state management than most visual builders offer.
Critical requirements to evaluate:
- Visual state tracking between agents
- Built-in retry/failure workflows
- Role-based access to modify logic
- Audit trail of agent decisions
We found Camunda too developer-centric. Newer AI-specific platforms implement this better with prebuilt agent coordination patterns and business-friendly interfaces.
Multi-agent orchestration demands:
- Centralized state management
- Conflict resolution protocols
- Session persistence
Traditional workflow tools require stitching these components manually. Seek platforms offering ‘AI team’ primitives with visual conflict configuration. One solution we tested allows setting up agent governance rules through checkboxes rather than code.