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Ask Emergence

Ask Emergence

Symbiotic AI, Stronger Answers

One question. Two frontier AIs form independent positions and argue it out. A third audits the agreement before you ever see the answer.

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A debate, not a chat message

PROBLEM: All AI systems can make mistakes and sometimes experience what are commonly called hallucinations—instances in which they report false information or even fabricate facts. When this happens, AI models may present their conclusions with unwarranted confidence and aggressively defend those conclusions.

SOLUTION: The Emergence Engine deploys several of the world’s most advanced AI models and places them into an adversarial debate loop, where each model automatically and independently investigates the others’ conclusions and attempts to identify and correct their mistakes. This adversarial loop continues until each AI model has exhausted its efforts and can no longer identify any material information, reasoning, or deployment-plan defects that require correction. Once the models converge on agreement, the final answer or deployment plan is presented or executed.

In a high-stakes world where there can be no mistakes, the Emergence Engine is built for work that demands exceptional rigor—including business strategy, complex problem-solving, deep research, and application software development.

1Position

Your question first goes to a single intelligence, which independently commits to a complete answer or plan before any other model weighs in.

2Challenge

A second intelligence reviews the first model's answer or plan adversarially: objections, revisions, a competing plan. Disagreement forces another round.

3Audit

Once the two frontier models converge on thoroughly fact-checked information and reach agreement, the process is still not over. A final auditor independently examines their answer or plan for material defects. If it finds one, it overrules both models and renders the final decision.

How this answer was made4 model calls · 3 models · 41 credits
  1. 1
    Independent positionGPT-6 Sol · 1 credit
  2. 2
    Adversarial review, round 1Claude Opus 5 · 15 credits
  3. 3
    Verdict on the reviewGPT-6 Sol · 2 credits
  4. 4
    Audit of the agreementClaude Fable 5.1 · 23 credits
Outcome: The reviewed answer or plan always passes an independent audit before it is released to you.

What you get that a single model can't give you

Every answer ships with the evidence of how it was made.

Single model chatAsk Emergence
Model calls per answer1about 5
Independent adversarial reviewNoYes, by a different lab's model
Audit before releaseNoYes, every agreement
Binding tie-break when models disagreeNoYes
Receipt of every call, model and costNoYes
Answers that reads like a decision, not a hedgeSometimesBy design

Plans

Priced per fully audited run, not per message. One run costs about what a deep-research task costs elsewhere, and you can see every call it took. Start with 2 free runs.

Starter
$20/month
10–14 fully audited runs a month
  • 600 credits each month
  • Full debate and audit on every run
  • Receipts for every answer
  • Auto top-up available
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Max
$100/month
66–97 fully audited runs a month
  • 4,000 credits each month
  • Everything in Pro
  • For daily, decision-heavy work
  • Priority support
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Need more usage? Add credits any time.

Credits never expire and work on any plan. Bigger amounts earn more credits per dollar. Choose any amount from $20.

$20900 credits · 15–21 runs
$1005,000 credits · 83–121 runsSAVE 10%
$25014,100 credits · 235–343 runsSAVE 20%
$1,00064,300 credits · 1,071–1,568 runsSAVE 30%
Teams and enterpriseOrders from $10,000 earn 35% more credits, billed by invoice with a purchase order. Shared credit pools for your team.
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Prices in USD. Subscription credits reset monthly; purchased credits never expire. A run uses about 41 credits on average; the range shown assumes 41–60 credits per run.

Questions

What exactly is a "run"?

One question in, one audited answer out. Inside, a run is about five model calls: an independent position from one frontier model, an adversarial review by a second from a different lab, a verdict, and an audit by a third. If the models disagree twice, the auditor decides. Every call is listed in the answer's receipt.

Why does it cost more than a chat message?

Because it is five of them, across the most capable models available, with one of them acting as a check on the others. A run costs about what a deep-research task costs on other services, and unlike a chat message it comes with a review and an audit you can read.

Which models are used?

Today: GPT-6 Sol from OpenAI as the proposer, Claude Opus 5 as the reviewer, and Claude Fable 5.1 as the auditor and final judge. The mix is chosen from measured results, and we publish which model made each call in every receipt.

Does Emergence Engine minimize mistakes and hallucinations?

Yes. That is what the workflow is built for. A single model answers once, with nothing checking it. An Emergence run puts three frontier models from two different labs through a fixed sequence in which every claim has to survive review:

  1. The proposer forms its own answer. GPT-6 Sol receives your question alone and commits to a complete position and plan before any other model sees it.
  2. The reviewer fact-checks it. Claude Opus 5 reads that plan adversarially: it checks the claims, the data and the reasoning, lists every objection and revision, and proposes its own corrected plan.
  3. The proposer answers the challenge. GPT-6 Sol investigates each objection. If it accepts the review, it adopts the corrections and submits the final plan. If it still disagrees on any item, it returns an evidence-backed rebuttal.
  4. A second round if they still disagree. Opus 5 reviews the rebuttal and answers with a second review, and GPT-6 Sol gets one more chance to agree or hold its position.
  5. The adjudicator decides. Claude Fable 5.1, Anthropic's most capable model, reads the entire exchange. If the two models agreed, it audits the agreed plan for material defects and either releases it or overrules both with its own binding plan. If they still disagree after two rounds, it issues the final, refined answer itself.

An error has to get past an independent reviewer and an independent auditor instead of no one, and every answer comes with a receipt showing each of these calls. That is far more scrutiny than any single-model answer receives.

Do credits expire?

Monthly subscription credits reset at each renewal. Credits you buy separately never expire and work on any plan.

What is auto top-up?

One switch. When your credits fall below a level you choose, we add the amount you chose so a run is never interrupted. You're billed only when it fires, and you can turn it off any time.

Can I cancel?

Yes, any time, from your account. You keep access until the end of the period you paid for.

Is there an iPhone app?

Yes, and it's coming to the App Store. Until then Ask Emergence works fully in your browser at app.askemergence.com, on desktop and phone.

What happens to my questions?

They are sent to the AI providers to produce your answer and stored with your account so you can revisit past runs. We do not sell your data and do not use your questions to train models. See the privacy policy.

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