Welcome to Council AI
Get insights from multiple AI models working together.
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What Council AI is, and why a panel beats a single chatbot
Most AI tools hand you one answer from one model and leave you to trust it. Council AI takes a different route. When you ask a question, it convenes a small panel of leading AI models and has each one answer on its own, without seeing what the others wrote. Those answers are then stripped of their labels and passed back around so every model can critique and score the rest. Finally a “Chairman” model reads the whole debate and writes a single, well-supported answer that reflects where the panel agreed, flags where it didn't, and tells you how confident the group actually was.
The point of all this is simple: one model repeats its own blind spots, but a group that independently lands on the same conclusion is a much stronger signal — and when the group splits, you get to see the disagreement instead of a single confident guess. It's the difference between asking one friend and asking a room.
How to use it, step by step
- 1Type your question. Enter anything you'd normally ask an AI — a decision, a research question, a piece of writing to critique. There's nothing to install and you can start as a guest.
- 2Let the panel answer. Each model on the roster responds independently. You'll see a short progress view while they work — usually a matter of seconds.
- 3Watch the peer review. The answers are anonymised and the models score each other on accuracy, completeness, reasoning and risk. No model is allowed to vote for itself.
- 4Read the Chairman's synthesis. You get one final answer with a confidence score, the points of agreement, the open disagreements, and suggested next steps.
- 5Dig deeper if you want. Every raw answer and every review is saved, so you can open the full transcript, export it to Markdown, or run a follow-up.
A worked example
“Should a two-person startup switch from seat-based pricing to usage-based pricing next quarter?”
Three models answer separately. Two lean towards a phased switch; one warns it could spook existing customers who like predictable bills.
In peer review, the cautious answer scores highest on risk-awareness, while a rival scores highest on completeness for laying out a migration path.
The Chairman combines them: recommend a hybrid rollout, grandfather current customers, and pilot usage-based pricing with new signups first — with an 72% confidence note and a flag that the answer depends on your churn tolerance.
Common ways people use it
Pricing, hiring, whether to take an offer — questions where a second and third opinion genuinely change your thinking.
When you're outside your expertise, agreement across models is a useful sanity check, and visible disagreement tells you where to dig.
Get several takes on a piece of writing, then a synthesised version that keeps the best lines and fixes the weak ones.
Have a panel weigh in on an approach, an architecture, or a tricky bug, and surface the risks a single model would gloss over.
Frequently asked questions
Yes. Guests can run councils of up to three models with no account, and a free account unlocks more. Premium adds larger seven-model councils and every template.
The roster is built from the providers we have access to — models from Google, Groq, OpenRouter and others. If a model is slow or unavailable, the council adapts rather than failing.
Not always, but it usually means a more balanced one. A bigger panel surfaces more perspectives and makes lone errors easier to catch.
No — consensus is a signal, not proof. Models can share blind spots. Every result shows a confidence score and a risk section, and important claims should always be verified independently.
Your prompts and results are saved to your account so you can revisit them, and are processed by the AI providers to generate answers. See our Privacy Policy for the full picture.