One AI agrees with your storyline. The client will not.
Deepest sends your recommendation to several top AI models at once and shows you exactly where they disagree. Your product is a recommendation that survives an adversarial review, and the disagreement between models is that review, run before the partner meeting instead of during it.
200 free credits. No credit card required.
Watch three models stress-test the same recommendation
One market-entry recommendation, three top models, three different attacks. Each one is a question you would otherwise hear for the first time in the room.
Simulated demo for illustration. Actual responses are more detailed and personalized.
Why one AI is not enough in consulting
A single chatbot is a very agreeable analyst: it takes your framing and extends it. What a recommendation needs before it ships is the opposite.
Your product is whatever survives the review
A recommendation is worth what it withstands. The partner meeting, the steering committee, the client Q&A: each is a structured attempt to break your logic, and clients pay precisely because it holds. A single model extends your storyline and almost never attacks it. Several models answering independently attack it from angles you did not choose, which is what a real review does.
One model means one framing, invisibly
Every model has habits: a default structure, a default set of considerations, a default shape of recommendation. Use one and your work quietly inherits its blind spots, and you cannot see them because there is nothing to compare against. Three independent takes on the same problem make each framing visible as a choice rather than the truth.
The objection you did not price is the expensive one
Getting surprised in the room costs more than any analysis that would have prevented it, because what the client discounts is not the slide, it is you. When three models read the same recommendation, the objection one raises and the others miss is exactly the dangerous kind: real enough to state plainly, non-obvious enough that you skipped it.
How consultants use Deepest
Three ways to combine the models, mapped to how consulting work actually gets pressure-tested.
Debate · models argue and converge
Debate: the partner meeting before the partner meeting
Debate makes the models argue against each other and converge over rounds. Put your recommendation in and watch what survives contact. The objections that emerge are a preview of the client's Q&A, and the position left standing, with its caveats now explicit, is the one that belongs on the summary slide. For a profession whose deliverables face a hostile audience by design, this is the mode to start with.
GPT-5.6 · opening
Claude · rebuttal
GPT-5.6 · concedes
Claude · holds
Debate
Positions converge after two rounds: acquisition, but only under a price ceiling.
Compare · where the models agree and disagree
Compare: independent reads on the same problem
Ask once and every model answers side by side, with an automatic breakdown of where they agree and where they split. Use it on market sizing, competitive dynamics, and any analysis where the real risk is a hidden assumption. Agreement across models is a sanity check, not proof; disagreement is a precise list of what to pressure-test before the client does.
GPT-5.6
Claude
Attributes churn to pricing, not product
Gemini
Compare
Two of three blame onboarding. The dissent is your next client interview.
Synthesis · one combined best answer
Synthesis: one deliverable from the strongest parts
For deliverables you rarely want three drafts; you want the best one. Synthesis has the models answer independently, then merges the strongest structure and cleanest argument into a single draft. Executive summaries, slide narratives, and workshop pre-reads arrive already cross-pollinated instead of shaped by one model's habits.
GPT-5.6
Claude
Gemini
Synthesis
One draft, assembled from the strongest sections of each answer.
What consulting work looks like with a model panel
Four places consultants put Deepest to work on day one. Each prompt is copyable as written.
Red-team before delivery
Run the recommendation past several models before the client sees it. Each attacks a different assumption, and the disagreement report is a ranked list of what to fix, caveat, or pre-empt in the appendix.
Try this prompt
Act as the client's CFO and attack this recommendation: name the three weakest assumptions, the strongest counter-recommendation, and the question I least want asked in the meeting: [paste recommendation]
Market and competitive analysis
Get independent first drafts of a landscape instead of one model's take. Where the models agree you have a working baseline; where they diverge is where the desk research and expert calls should go.
Try this prompt
Map the competitive landscape for mid-market warehouse automation in the DACH region: main players, how they win deals, pricing models, and where a new entrant could wedge in. Flag every claim that needs primary-source verification.
Structuring ambiguous problems
Three models will decompose the same messy client situation three different ways. Comparing the issue trees shows you which structure actually fits the problem, instead of committing to the first one that sounds MECE.
Try this prompt
Our client, a regional grocery chain, is losing share and does not know why. Build a MECE issue tree for the problem, then propose the three hypotheses you would test first and the data that would confirm or kill each one.
Deliverables and slide narratives
Turn findings into a storyline with action titles, or draft the executive summary in Synthesis mode so it reads like the strongest version of the argument rather than the first fluent one.
Try this prompt
Turn these findings into a 10-slide storyline using action titles: every slide title is a full sentence stating the takeaway, with two or three supporting points beneath it. Findings: [paste findings]
Start with 200 free credits and up to 2 models per prompt.
Confidentiality
Built for work under NDA
Conversations are encrypted in transit and at rest, are never used to train models, and you can export or permanently delete everything at any time. Prompts go to model providers through enterprise APIs, not consumer chatbots. Follow your firm's AI policy and each client's agreements, and anonymize client names and identifying figures where required; the stress-test works exactly the same on a sanitized version.
Questions consultants ask
Work in a different field? Deepest works the same way for product managers, marketers, lawyers, and every other profession.
Hear the objection before the client raises it
Start free with 200 credits. No credit card required.