One AI is an unreviewed source. Deepest puts every question to a panel.
Deepest sends your question to several top AI models at once and shows you exactly where they disagree. For work where a fabricated citation can end up in print under your name, the disagreement is the review layer a single chatbot never gives you.
200 free credits. No credit card required.
Watch three models review the same study design
One proposed survey, three top models, three different fatal flaws. Where they split is where Reviewer 2 will look.
Simulated demo for illustration. Actual responses are more detailed and personalized.
Why one AI is not enough in research
A single chatbot gives you one fluent answer with no way to tell the established from the invented. Your field already has a name for sources like that.
Fabricated references end up in print
Journals have retracted papers over AI-invented citations, and reviewers now actively hunt for them. The failure was never the drafting, it was trusting a single model with no cross-check. When several models answer the same question, a reference only one of them produces is a flag to pull the paper, not a footnote to paste.
One summary hides the controversy
A single model's literature summary reads as settled science because you cannot see what it flattened. Ask three models and the contested claims surface as disagreement: one calls the evidence strong, another calls it mixed, and now you know which parts of your related-work section need hedging and which need a deeper read.
You already know why one reviewer is not enough
No journal accepts a paper on a single review, because one reader misses things and brings their own biases. A single AI is one unreviewed reader. Deepest gives every question the panel treatment: independent answers, then an explicit report of agreement and dissent, for less than two separate subscriptions.
How researchers use Deepest
Three ways to combine the models, mapped to how research actually gets checked.
Compare · where the models agree and disagree
Compare: instant triangulation
Ask once and every model answers side by side, with an automatic breakdown of where they agree and where they split. Use it on empirical claims, literature questions, and any summary you are about to rely on. Agreement across models is not truth, but disagreement is a precise map of the claims to check against the actual literature before they reach your manuscript.
GPT-5.6
Claude
Cites a meta-analysis the others do not mention
Gemini
Compare
One citation appears in a single answer. Pull that paper before it enters your draft.
Synthesis · one combined best answer
Synthesis: one literature summary from three passes
For background sections and grant boilerplate you do not want three drafts, you want the best one. Synthesis has the models answer independently, then merges the strongest structure and cleanest prose into a single draft. Related-work sections, significance paragraphs, and lay summaries arrive already cross-pollinated instead of carrying one model's blind spots.
GPT-5.6
Claude
Gemini
Synthesis
One draft, assembled from the strongest paragraphs of each answer.
Debate · models argue and converge
Debate: meet Reviewer 2 before Reviewer 2 meets you
Debate makes the models argue against each other and converge over rounds. Put your study design or your central claim in and watch what survives contact. The objections that emerge are a preview of peer review, and the methodology left standing is the one worth running.
GPT-5.6 · opening
Claude · rebuttal
GPT-5.6 · concedes
Claude · holds
Debate
Positions converge after two rounds. The surviving design is the one to preregister.
What research work looks like with a model panel
Four places researchers put Deepest to work on day one. Each prompt is copyable as written.
Literature review and synthesis
Map a literature fast: several models outline the terrain independently, and the disagreement report shows which claims are contested. Treat every citation as a lead, not a source, and pull the paper before it enters your reference list.
Try this prompt
Summarize the current evidence on whether open-plan offices reduce productivity. Separate meta-analyses from single studies, note where findings conflict, and flag any citation you are not fully certain exists.
Methods and study design critique
A pre-submission red team. Each model independently attacks your design: identification, sampling, power, measurement, analysis plan. Three reviewers find three different weaknesses, months before the real ones do.
Try this prompt
Act as a skeptical methods reviewer. Critique this study design: name the single biggest threat to validity, then list every other flaw a reviewer would raise, each with the specific revision that fixes it: [paste your methods section]
Abstracts, grants, and revision
Abstracts, specific aims, significance sections, response-to-reviewer letters. Synthesis mode merges the models' drafts into one that is tighter and less templated than any single model produces, in your field's register.
Try this prompt
Revise this abstract to 250 words for a general-science journal. Keep every quantitative claim exactly as written, sharpen the motivation in the first two sentences, and end on the implication: [paste abstract]
Understanding unfamiliar methods
Interdisciplinary work means reading papers whose methods you never trained on. Ask three models to explain a technique and where it breaks: the overlap is the reliable core, and the differences tell you exactly what to read up on.
Try this prompt
Explain difference-in-differences estimation to a molecular biologist with basic statistics. Cover the parallel trends assumption, the common ways it fails, and how to read the results table in an economics paper.
Start with 200 free credits and up to 2 models per prompt.
Unpublished work
Built for work under embargo
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 institution's AI policy and your funder's data rules, and keep identifiable participant data out of prompts; the workflow works exactly the same.
Questions researchers ask
Work in a different field? Deepest works the same way for teachers, writers, consultants, and every other profession.
Give every claim a review panel
Start free with 200 credits. No credit card required.