Multi-model reasoning · Multi-agent debate

For questions that matter,
one model is
not enough.

RAG or fine-tuning — which is better for injecting domain knowledge?

Send the same question to the AI models you pick, compare the answers side by side, and let a mediator synthesize what they agree on, where they differ and where they contradict. When views split, the models debate until the options narrow. Get a thinking environment for decisions you can stand behind.

Made for
Researchers & analysts
When you need to stress-test the range of views
  • What is the biggest blind spot in this analysis?
  • How would someone on the opposing side read it?
  • Which important variable have I missed?
  • What evidence would refute this hypothesis?
  • What conclusions would different experts reach?
Made for
Decision makers
See where the evidence agrees and collides, before you commit
  • What's the argument against this hiring plan?
  • What risk does this market-entry strategy miss?
  • What pushback should we expect on this price increase?
  • If we were to stop this project, on what grounds?
  • How does this investment decision look in another frame?
Made for
AI power users
Compare how the models differ, directly
  • Why did GPT and Claude reach different conclusions?
  • Whose reasoning is more convincing?
  • What conclusion do the models share?
  • Which perspective did one model miss?
  • What answer emerges when you combine them all?
Made for
Founders & independents
Big calls you make alone, checked by many
  • Build first, or sell first?
  • Sell direct, or through partners?
  • Start narrow, or go broad?
  • Raise money, or bootstrap?
  • Pivot now, or push harder?
Why several models

AI sounds certain —
and that certainty has blind spots.

Every model has its own blind side: bias in its training data, missing recent information, a subtly different reasoning style. Look at one model alone and you can't even tell what it left out.

Today — single-model thinking
  1. 01You open another tab to check whether the first answer holds up.
  2. 02You compare the responses in your head and guess where they differ.
  3. 03Contradictions slip past unnoticed.
  4. 04In the end you pick whichever answer sounded best.
coThink — multi-perspective reasoning
  1. 01Ask once and get as many perspectives as you selected, on one screen.
  2. 02A mediator separates agreements, contradictions and unique insights.
  3. 03You see exactly where the models part ways.
  4. 04You decide for yourself, on top of a structured synthesis.
The cost of cross-checking

1% of users already
cross-check their models.

They're just doing it by hand — four tabs, the same question pasted four times, four answers reconciled in their head. Knowing that comparison is right doesn't mean you can pay that cost every time. coThink brings the whole process into one screen.

Today — several tabs
ChatGPT
Question: paste the same thing…
Claude
Question: paste the same thing…
Gemini
Question: paste the same thing…
Perplexity
Question: paste the same thing…
4 tabs opened·4 pastes·4 answers read separately
coThink — one screen
coThink
Question: asked once
ChatGPTClaudeGeminiPerplexityGrok
+ mediator synthesis · agreements / contradictions / conclusion
1 question·a structured synthesis
How it works

Three steps that complete
a line of thought.

Ask → multi-perspective answers → structured synthesis. That's how one question turns into a decision.

01
Ask once
Write the question once, switch on the brands you want answering, then pick which model each brand should use. The same question goes to the 2–5 models you selected, all at once. No tab-hopping, no repetition.
New thread
Where should we look first for this quarter's new market?
GPT-5 MiniGemini 3.1 Flash LiteClaude Haiku 4.5SonarGrok 4.3
📎 Image📄 Document🎙 Voice🌐 Web searchSend question
02
Surface the differences
The answers arrive as tabs on one screen. Compare them as they are, then pick a mediator and press '✨ Synthesize' — it breaks the responses down into agreements, unique perspectives and contradictions. Any model in the catalog can be the mediator; the default is GPT-5.6 Luna.
Model answers
GPT-5 MiniGemini 3.1 Flash LiteClaude Haiku 4.5

The key is a segment with low barriers to entry where references accumulate quickly.

1. Start with mid-market B2B SaaS — they decide fast, and each rollout becomes a sales asset.
2. Lower price sensitivity …

MediatorOpenAIGoogleAnthropicPerplexityxAIGPT-5.6 Luna
✨ Synthesize
03
Get a structured judgement
Synthesized answer · agreements · unique insights · contradictions · per-model contributions · follow-up questions, all at once. The raw material for a decision, always in the same shape.
✦ Mediator synthesisMediator: GPT-5.6 Luna
∷ Synthesized answer

A staged strategy — target mid-market B2B SaaS first to build references, then expand into enterprise — is the most balanced choice.

Shared view

All models put 'securing early references' first.

Unique insight

Perplexity cites current market size; Grok points to the competitive gap.

Contradictions

GPT says enterprise first, Claude says mid-market first — the target priority splits.

ContributionsGPT-5 MiniGemini 3.1 Flash LiteClaude Haiku 4.5
✦ Continue with a follow-up
What customer acquisition cost should we expect in the mid-market?How should we define the key metric for building references?
Multi-agent debate

When the models split,
let them argue it out.

If the synthesis shows a split, don't stop there. The models that answered your question rebut and revise each other in a single conversation, while a moderator judges convergence and delivers a conclusion you can act on. You watch, interject, and take the conclusion.

  • Participants and moderatorThe participants are every model that answered your question (two or more); the moderator is the mediator that handled the synthesis. There's nothing extra to choose.
  • Framing the cruxThe moderator turns the split into a single crux.
  • Taking turnsThe models go back and forth in short turns (three sentences or fewer), rebutting and revising each other directly.
  • A conclusion to decide onThe moderator sets out a final recommendation, the core reasoning and the conditions under which it holds.

This is a conversation, not a survey. At any point you choose to continue, conclude or stop, and a comment you leave is reflected in the next turn. The AI doesn't decide for you — it sharpens your judgement by pushing back.

Multi-agent debate
CruxNarrow the early target to mid-market B2B, or go straight to enterprise?
GPT-5 Mini

Enterprise first — the contracts are far bigger. Mid-market churns, so those references are worth less.

Claude Haiku 4.5

Enterprise sales cycles run six months or more. You need mid-market references first to open that door.

ModeratorThe two views split on 'speed vs. scale'. Let's narrow it using the early runway as the test.
Gemini 3.1 Flash Lite

Under twelve months of runway, mid-market first is the rational call — you can't survive the long sales cycle.

⚖ Moderator's conclusion

A staged strategy: start in mid-market B2B, secure references, then expand into enterprise.

Holds whenRunway is under twelve months — when fast cash flow comes first.
The coThink approach

Not a response —
a structure you can judge with.

Where a normal AI chat hands back a long paragraph, coThink hands back the structure a decision needs: what everyone agrees on, where things split, and what you should ask next — all visible at a glance.

Structured synthesisMediator: GPT-5.6 Luna
▸ Question

Which market should we target first with a new B2B SaaS product?

GPT-5 MiniGemini 3.1 Flash LiteClaude Haiku 4.5SonarGrok 4.3
+ Agreement
All 5 models that answered named 'researchers and analysts' as the first target.
+ Contradiction
The models disagree on price sensitivity — needs verification.
+ Best answer
Ship the first version for researchers, on a single pricing tier.
▸ Follow-up questionsHow do we verify price sensitivity? →Where are competitors weak? →Which go-to-market channel? →
01
Agreements
What every model agreed on. The most reliable place to start.
Every model that answered ranked 'B2B SaaS researchers' as the first market.
02
Unique insight
A point only one model raised. The clue that fills a blind spot.
Perplexity: recent industry reports mention 'ensemble reasoning', up 212% year over year.
03
Contradictions
Where the models part ways. The part you have to judge yourself.
Grok rates price sensitivity 'low'; Claude rates it 'moderate or higher'.
04
Best answer
A single conclusion, weighted and synthesized across every response.
→ Recommend shipping the first version for researchers and analysts, on a single tier.
05
Contribution map
Which model contributed what, and on what grounds.
Point A → GPT, Claude · Point B → Perplexity · Counterpoint → Grok
06
Follow-ups
Three suggested questions to carry your thinking forward.
1) How to verify price sensitivity? 2) Where are competitors weak? 3) Which channel?
Choosing models

Which models do the thinking?
You decide.

OpenAI · Google · Anthropic · Perplexity · xAI — 25 models across 5 brands, all in the same interface. Switch brands on and off, pick which model each brand uses, then send one question to 2–5 models at once.

01Askpick 2–5
Who answers the question
Switch on the brands you want answering and pick which model each one uses — anywhere from two to five per question.
02Synthesizepick 1
Who synthesizes it
Pick one mediator to break the answers down into agreements, unique perspectives and contradictions. Any of the 25 models in the catalog can take the role.
03Debateautomatic
Who moderates
The mediator that handled the synthesis carries straight on as the debate's moderator. The participants are every model that answered (two or more).
The models you pick from — 25 across 5 brands
OpenAI
6 models
On by default
GPT-5 Minidefault
빠르고 저렴한 경량
GPT-5.1GPT-5.2GPT-5.6 LunaGPT-5.6 Terra ProGPT-5.6 Luna Pro
Google
6 models
On by default
Gemini 3.1 Flash Litedefault
초경량·최저 비용
Gemini 3.1 ProGemini 3.5 FlashGemini 3.6 FlashGemini 3.5 Flash LiteGemini 3.7 Flash
Anthropic
6 models
On by default
Claude Haiku 4.5default
초고속·저렴
Claude Sonnet 4.6Claude Opus 4.8Claude Sonnet 5Claude Opus 5 (Fast)Claude Opus 5
Perplexity
4 models
Optional
Sonardefault
경량 웹 검색
Sonar ProSonar Reasoning ProSonar Pro Search
xAI
3 models
Optional
Grok 4.3default
실시간성·긴 컨텍스트
Grok 4.5Grok 4.6
Use cases

For every moment
that needs a judgement.

coThink is a thinking environment for making decisions properly. Reach for it when an important call is yours alone and it has to be quick.

Strategy
Reviewing business strategy
Pricing models, market-entry timing, resource allocation — decisions that need a counter-argument, contrasted across several perspectives fast.
Learning
Getting up to speed fast
In an unfamiliar domain, reading several models' explanations together gets you to the core without tilting toward any one framing.
Review
Pressure-testing your writing
Paste in your draft or proposal and collect critical feedback. Instead of smooth agreement, you get objections from a different vantage point.
Research
Widening a research angle
The frames, sources and counter-examples one model missed get filled in by another. Especially useful at the start of a research effort.

Not a faster answer —
a better judgement.

The next time a decision deserves more than one opinion, start here.