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Glossary

Ensemble Intelligence
Independent answers, combined.

In short

The collective intelligence that emerges when multiple AI experts with diverse training data, reasoning frameworks, and cognitive profiles analyze the same problem independently before their outputs are synthesized. Inspired by ensemble methods in machine learning — where combining multiple weak models produces a strong one — ensemble intelligence in decision-making produces recommendations that are more robust, nuanced, and calibrated than any single expert could achieve alone.

Last reviewed

The full definition

The key requirement is genuine diversity: each expert must differ in how they think, not just what they say.

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.