Common patterns
- Orchestrator and specialists — a lead agent splits the task and assigns parts to specialist agents.
- Pipeline — each agent does one stage and passes the result on.
- Reviewer — one agent produces, another checks quality or compliance.
When is multi-agent AI worth it?
When a process has clearly different skills or steps (research, analysis, writing, checking), large volumes, or strict review needs. For a single, well-defined job, one agent with good tools is simpler, cheaper and easier to test.
What does it cost?
A platform with several agents, enterprise integrations and data pipelines is typically a Large project at Agentic AI Tech Hub — $20,000–$45,000 one-time, usually 6–9 months — as a rough guide. See AI agent development cost.
Frequently asked questions
Is multi-agent AI more accurate?
It can be, when specialised agents and a reviewer catch each other’s mistakes, but it also adds complexity that must be tested.
Do agents share memory?
They can share task state through the orchestrator or a common store, with permissions limiting what each one sees.