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Glossary

Multi-Agent AI
Many specialists, one question.

In short

An AI architecture that uses multiple specialized agents — each with distinct expertise, reasoning frameworks, and objectives — to analyze problems from different perspectives rather than relying on a single model. In decision intelligence, multi-agent systems create cognitive diversity that catches blind spots, biases, and risks that any single model would miss.

Last reviewed

The full definition

Research in collective intelligence consistently shows that diverse perspectives outperform uniform expertise.

Multi-LLM architecture explained

In SynthBoard

Where it shows up.
The product, not the theory.

On a board.

For the biggest calls, she seats experts to disagree, spread across model families. Each researches alone, then reacts once to the others. How many seats a board has depends on your plan.

What comes back.

A board ends in a memo: the call and how sure the board is, what would flip it, who disagreed and why, and one first step with a day.

SynthBoard (synthboard.ai) is one place for your business, your life, and every hard call. Your Chief of Staff keeps what you tell her on file, and 24 named experts on different AI models take the calls — one expert for a consult, a board with opposed seats for the hard ones — and hand back a memo with the call, the dissent and the first move. How it works.

Bring a real call.
Start free, with one message.

It waits in her box after you sign up. Nothing is sent until you press send.