Why multi-agent AI systems fail in production
Most multi-agent demos work and most multi-agent deployments do not. The reason is error compounding — and the fixes are structural, not model upgrades.
Paperclip, CrewAI, AutoGen and n8n: what each is genuinely good at, what self-hosting really costs, and when open source is the wrong answer.
Open source dominates this category, and for technical teams it is usually the right call. The licence is free. The running is not.
MIT licensed. Solves the organisational layer — org charts, delegation, budgets, governance, audit trails, company templates. Runtime-agnostic. Closest thing to a company rather than a script. Full comparison.
Role-playing crews with clean abstractions and a large community. Fastest of these to a working prototype. Full comparison.
Microsoft's conversational multi-agent framework, strong for research. Worth noting Microsoft has moved active development toward the Microsoft Agent Framework. Full comparison.
Source-available workflow automation with AI nodes. Best of these for deterministic, auditable pipelines. Full comparison.
When nobody on your side wants the job. Free software with no operator is not cheaper — it is an unfinished project with a monthly hosting bill.
We run Paperclip so our clients never have to. See all nine comparisons.
Most multi-agent demos work and most multi-agent deployments do not. The reason is error compounding — and the fixes are structural, not model upgrades.
CrewAI, LangGraph and n8n sell you the ability to build. Managed services sell you the system running. A buyer's guide to picking the right layer.
Agentic AI, stripped of jargon: software that does jobs on a schedule instead of waiting to be asked. What changes, what does not, and what to ignore.
We build the agent team, connect it to your accounts and supervise the output. Twenty-minute call · See pricing