Multi-Agent System
An architecture where multiple specialised AI agents collaborate, each with its own role, tools, and scope.
What is Multi-Agent System?
A multi-agent system divides complex work across agents: one retrieves, one reasons, one validates, one acts. This decomposition improves reliability and auditability — each agent has a narrow scope and can be evaluated independently. See Multi-Agent Systems and Secure Multi-Agent Networks.
Why it matters for on-premise & regulated AI
Multi-agent systems raise a governance question single agents do not: who is accountable when agents delegate to each other? In regulated environments the answer must be reconstructable from logs — which agent acted, on whose request, with what data. Hosting the whole system on-premises gives you one coherent, exportable trace across all agents instead of fragments scattered across vendor clouds.
Read the full guide: Multi-Agent System — in-depth article →
Related terms
Putting Multi-Agent System to work?
VDF AI runs governed AI agents on your own infrastructure — on-premises, sovereign cloud, or air-gapped. Book a working session to map the architecture.
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