Collaborative intelligence

Don't settle for the first answer.

Ask once. Dr Moot convenes a panel of leading AI models to challenge the answer and each other, expose what's missing and deliver a considered verdict.

Start a mootSee the deliberation

The deliberation

Watch the answer earn its place.

Every moot runs in the open. Seats draft, challenge and verify in real time, and the transcript keeps every claim - contested or settled - on the record.

Every seat visible

Generator, Sceptic and Specialist work in parallel, each badged with the lab and model holding the seat.

Dissent on the record

Contested claims stay in the transcript with the vote that split the panel.

A verdict you can audit

The Chair’s ruling links back to the rounds, votes and sources that produced it.

From the dictionary

moot /muːt/ विशेषण 1. विवादास्पद। चर्चा के अधीन। 2. व्यावहारिक महत्व से रहित; विशुद्ध रूप से सैद्धांतिक। क्रिया 1. चर्चा के लिए प्रस्तुत करना; उठाना। 2. बहस करना। संज्ञा 1. विचार करने और निर्णय लेने के लिए बुलाई गई लोगों की सभा; परिषद या बैठक। (पुरानी अंग्रेज़ी mōt, gemōt)

The premise

Should one model mark its own homework?

A single model states its mistakes with confidence. A panel catches false positives before they reach you.

False positives are confident

Any single model has blind spots and can state mistakes with the same confidence as facts - there is no signal telling you which is which.

Every answer, equally confident4 were wrong

Scrutiny, built in

A sceptic challenges the draft, independent labs cross-check it, and only the answer that survives scrutiny is presented - a second opinion by default.

Claims surviving scrutiny0 of 5

Two claims withdrawn under challenge before the verdict.

Independent seats

Each seat is held by a different lab, so the models genuinely check each other.

Dissent stays visible

The transcript keeps what was claimed, contested and decided on the record.

High stakes, flagged

Auto spots consequential questions and routes them to deeper deliberation.

Challenged by design

A dedicated sceptic attacks the draft’s assumptions instead of politely agreeing with it.

Checked by independents

Models from separate labs cross-examine each other’s claims, so shared blind spots surface.

Verified against sources

Search agents check surviving claims against real evidence before the Chair rules.

इनके फ्रंटियर मॉडलों के साथ विचार-विमर्श

OpenAI logoOpenAI
Anthropic logoAnthropic
Google logoGoogle
xAI logoxAI
Mistral logoMistral
Meta logoMeta
DeepSeek logoDeepSeek
Moonshot AI logoMoonshot AI
Qwen logoQwen
Z.ai logoZ.ai
Perplexity logoPerplexity
NVIDIA logoNVIDIA
Hugging Face logoHugging Face
Cerebras logoCerebras
Groq logoGroq
Cohere logoCohere
OpenAI logoOpenAI
Anthropic logoAnthropic
Google logoGoogle
xAI logoxAI
Mistral logoMistral
Meta logoMeta
DeepSeek logoDeepSeek
Moonshot AI logoMoonshot AI
Qwen logoQwen
Z.ai logoZ.ai
Perplexity logoPerplexity
NVIDIA logoNVIDIA
Hugging Face logoHugging Face
Cerebras logoCerebras
Groq logoGroq
Cohere logoCohere

The panel

Every seat has one job.

Change any prompt. Assign any model. Save the panel and convene it again.

Illustrated portrait of the Generator seat
Generator

Commits to the strongest complete answer and states its assumptions so the panel can attack them.

Illustrated portrait of the Sceptic seat
Sceptic

Finds factual errors, unsupported assumptions and the logical gaps that could change the answer.

Illustrated portrait of the Specialist seat
Specialist

Checks facts, figures, definitions and sources, separating evidence from inference.

Illustrated portrait of the Chair seat
Chair

Weighs the strongest arguments left standing and delivers one clear, actionable verdict.

How it works

One question. A proper hearing.

Watch each claim get drafted, contested and refined. The transcript shows the working exchange, while dissent remains visible.

Ask

input

Give the panel your question, context or document once.

Deliberate

process

Models take defined roles and challenge each other in real time.

Thinking · 3 seats

GeneratorGPT-5.6-sol

Cross-review round 2

SUMMARY

Recommendation Do not ban social media for all UK under-16s. The governmen…

The Sceptic and Specialist reinforce my position: causal evidence for population-level harm reduction from a blanket ban is insufficient, while evasion, displacement, privacy costs, and lost benefits are material.

ScepticClaude Sonnet 5

Cross-review round 2

SUMMARY

Where the panel agrees (and why it holds) All three of us independently reject …

Both Generator and Specialist converged on “no blanket ban, regulate design/features” - matching my prior position. No one defended a full ban, so the panel has reached consensus.

SpecialistGrok 4.5

Cross-review round 2

SUMMARY

Established evidence Large correlational datasets (Millennium Cohort, YRBS,…

Generator correctly prioritises feature-level duties and privacy-preserving assurance over prohibition; their displacement claim matches my enforcement data.

Verify

evidence

Claims are checked against sources before the Chair reaches a verdict.

Verification Round 1

Complete

Checked 3 contested claims:

  • France and Nordic countries retreated from wealth taxes
  • The top 1% own ~40% or more of global wealth
  • No modern market democracy has sustained a wealth ceiling

Used 9 sources

en

Why are France’s top earners leaving and where are they going? | Euronews

euronews.com

F

Before California, France tried a wealth tax. Rich people fled instead | Fortune

fortune.com

O

World’s top 1% own more wealth than 95% of humanity, says Oxfam

oxfam.org

Decide

output

The Chair weighs what survives and returns one actionable verdict.

Chair verdict

No formal enterprise-harness standard exists yet. Harness quality, not model choice, is what determines the outcome.

Panel agreement

Unanimous

3 of 3 positions in

Chair confidence

Medium

Held at medium because three claims rest on vendor material alone.

Contested · 0:20

The disagreement is about confidence, not the conclusion - Sceptic wants the adoption claims rated Medium.

Choose the depth

Not every question needs a panel.

By default Dr Moot chooses the right process: Solo answers directly, Review improves one answer, Debate tests opposing sides, and Moot convenes the full panel.

Anthropic logo

Solo

One model answers directly for quick, low-stakes questions.

OpenAI logo
Google logo

Review

One answer is drafted, independently challenged, revised and judged.

Anthropic logo
OpenAI logo
xAI logo

Debate

Affirmative and Negative argue opposing sides and a Chair decides.

Anthropic logo
OpenAI logo
Google logo
Mistral logo

Moot Council

Generator, Sceptic and Specialist deliberate toward one chaired verdict.

Built for consequential work

Where missing one thing costs more than asking twice.

Consensus check round 1

Complete

Panel did not reach a stance

91%

CONTESTED · 1

Generator's analogy that ‘taxation already limits property rights’ fully rebuts the libertarian objection that a near-100% marginal cap is categorically different from ordinary taxation.

63%*
1 agree·1 disagree·1 abstain

AGREED BUT UNRESOLVED · 3

Whether Generator's ‘ethically defensible in principle’ claim should be explicitly labeled as Rawlsian-leaning rather than presented as framework-neutral (Sceptic raises this as a load-bearing unsupported assumption).

AGREED AND RESOLVED · 4

A hard maximum wealth cap is ethically permissible in principle under at least some normative frameworks.

1 agree·0 disagree·2 abstain

Strategy & product

Market entry, build versus buy, pricing and operating choices.

Documents & contracts

Find one-sided clauses, unusual terms and costly omissions.

Technical review

Challenge architecture and code instead of politely summarising it.

Research & analysis

Stress-test claims, sources and counter-arguments before publishing.

अक्सर पूछे जाने वाले सवाल

कोई सवाल है? हमारे पास जवाब है।

Dr Moot आपके सवाल पर विचार करने के लिए अग्रणी AI मॉडलों का पैनल बुलाता है। किसी एक मॉडल के पहले जवाब पर भरोसा करने के बजाय, पैनल मसौदा तैयार करता है, उसकी समीक्षा करता है और तब तक संशोधन करता है जब तक भरोसेमंद सर्वसम्मत जवाब न मिल जाए।

LLM काउंसिल - जिसे कभी-कभी AI मॉडल काउंसिल भी कहा जाता है - कई बड़े भाषा मॉडलों का एक पैनल है जो किसी सवाल पर मिलकर विचार-विमर्श करता है, बजाय इसके कि एक अकेला मॉडल जवाब दे: मॉडल मसौदा बनाते हैं, एक-दूसरे की आलोचना करते हैं और मतदान करते हैं, और एक अध्यक्ष फ़ैसला सुनाता है। Dr Moot एक उत्पाद के रूप में LLM काउंसिल है। यह स्वतंत्र प्रयोगशालाओं के मॉडलों को बुलाता है, उनसे एक-दूसरे के जवाबों को चुनौती दिलवाता है, और आपको नतीजे के पीछे की सहमति, असहमति और भरोसा दिखाता है।

हर अकेले मॉडल के कुछ अंधे क्षेत्र होते हैं और वह गलती को भी विश्वास के साथ बता सकता है। moot में एक संशयवादी मसौदे को चुनौती देता है, स्वतंत्र लैब के मॉडल एक-दूसरे की जाँच करते हैं और केवल जाँच में टिकने वाला जवाब प्रस्तुत किया जाता है - यानी दूसरी राय पहले से शामिल होती है।

Relay आपके सवाल को क्रम से मॉडलों के बीच भेजता है - एक मसौदा बनाता है, दूसरा समीक्षा करता है और पहला संशोधन करता है। Debate में मॉडल एक साथ अपने तर्क रखते हैं। Moot पूरा पैनल बुलाता है - Generator, Sceptic और Specialist - और Chair सर्वसम्मति बनने तक विचार-विमर्श के दौर संचालित करता है।

नहीं। Dr Moot हर सवाल को डिफ़ॉल्ट रूप से सबसे उपयुक्त मोड में भेजता है और अधिक गहन विचार-विमर्श के लिए उच्च जोखिम वाले सवालों को अपने-आप चिह्नित करता है। आप चाहें तो हमेशा मोड स्वयं चुन सकते हैं।

पैनल में OpenAI, Anthropic, Google, xAI और Mistral सहित स्वतंत्र लैब के फ्रंटियर मॉडल शामिल होते हैं। हर सीट अलग लैब के मॉडल को दी जाती है ताकि वे सच में एक-दूसरे की जाँच करें; कोई मॉडल उपलब्ध न हो तो दूसरी लैब का विकल्प अपने-आप शामिल हो जाता है।

यदि आप हमारे उत्पाद से संतुष्ट नहीं हैं तो हम 30 दिनों की धन-वापसी गारंटी देते हैं।

आप बिलिंग पेज पर जाकर अपनी सदस्यता रद्द कर सकते हैं।

हाँ, आप बिलिंग पेज पर जाकर कभी भी अपना प्लान बदल सकते हैं।

हाँ, हम 14 दिनों का मुफ़्त ट्रायल देते हैं।

Convene the panel

Bring a question
worth arguing about.

One prompt in. The strongest surviving answer out.

Start a moot

शीघ्र पहुँच सूची में शामिल हों

Dr Moot के दरवाज़े खुलते ही सबसे पहले शामिल हों - जगह उपलब्ध होने पर हम आपको आमंत्रण भेजेंगे।