ReviewOS
250M+ papers indexed

Enter your topic.
Understand why
science disagrees.

ReviewOS searches hundreds of millions of papers and returns not just what the literature says — but why the debate looks the way it does. Methodology conflicts. Funding bias. Research gaps. All surfaced automatically.

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Live query
Does omega-3 reduce cardiovascular events?
AI Assistant
0.89 confidence · 47 sources
Strong evidence from 3 meta-analyses (2021–2023, n=4,200) supports benefit in secondary prevention. Disagreement stems from primary prevention cohorts where effect sizes are smaller and dose-response relationships are unclear.
[1] Rischitelli GD et al. — Am J Clin Nutr, 2021
[2] Bhatt DL et al. — NEJM, 2019
● 250M+ articles indexed
doi.org/10.1056/nejmoa1811403
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Indexed by
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En chiffres

A research instrument, not a chatbot.

From systematic review to field decisions — same evidence base, adapted to how you work.

240K+
Peer-reviewed papers indexed across major databases.
2,400+
Researchers actively using ReviewOS for their reviews.
18K+
Literature reviews generated by our AI assistant.
01

Know where the field stands.
Before you build on it.

Every paper contributes to a picture. ReviewOS reconstructs that picture so you can see the shape of scientific agreement — not just the headline result.

Consensus reached

When multiple independent replications point the same direction, ReviewOS shows you the strength and breadth of agreement — and which domains are tested.

Active debate

When studies contradict, ReviewOS doesn't flatten the nuance. It surfaces the disagreement, explains what's driving it, and identifies which papers you can trust more.

Unresolved

Not every question has an answer yet. ReviewOS distinguishes between genuinely contested science and questions that simply haven't been studied properly.

02

The cause of disagreement
is the most valuable signal.

Every other tool tells you that studies conflict. ReviewOS explains why — so you can judge the literature yourself and decide where to push the field forward.

Methodology conflict detector

Automatically identifies when studies disagree because of sample size, measurement instruments, population differences, or statistical approaches.

Funding bias flags

Cross-references study funding sources. When industry-funded studies consistently reach different conclusions, you see it — with the numbers.

Geographic & demographic gaps

Surface when evidence comes predominantly from specific populations and what that means for generalizability to your patient, context, or country.

03

Every gap is a research question.
Find them before your reviewers do.

ReviewOS doesn't just show you what exists — it identifies what's missing. This is where the real contribution lies: finding the space where your work can move the field forward.

Unexplored intersections

Where two or more well-developed fields meet but haven't been combined? ReviewOS finds these — they often generate the most novel findings.

Population coverage gaps

Shows you which demographics are over- or under-represented in current evidence, and what that means for your study's external validity.

Methodological gaps

Identifies where the dominant study design has left qualitative or mixed-methods questions completely unanswered.

Nexus — Live Query

Living review — updates automatically

Most tools give you a snapshot. ReviewOS gives you a living document. New papers refine the consensus, debates shift, and gaps move.

Your question
Does omega-3 supplementation reduce cardiovascular events in high-risk patients?
Consensus state
68% support
19% nuance
13% unclear
Why the debate exists
Methodology RCT heterogeneity: dose (1–4g), EPA/DHA ratio, population selection
Bias 43% of positive trials funded by omega-3 manufacturers
Gap No long-term (>5yr) RCTs in primary prevention populations
47 papers analyzed
12 supporting · 6 contradicting · 29 contextual
AI confidence: 0.89
Why build ReviewOS now?

Every tool tells you what the literature says.
None explain why the debate looks the way it does.

Every tool tells you what the literature says. None explain why the debate looks the way it does. That gap is real and unaddressed.
2 million+ papers published annually. Manual literature review can't scale. AI can — if you build the right causal layer on top of the data.
Living review formats are gaining traction (Living Evidence Maps, COVID-NMA). The infrastructure is ready. The synthesis layer is missing.
GDPR-compliant, EU-based. French Ministry of Higher Education just backed OpenAlex — the data infrastructure ReviewOS runs on. Timing is good.
Market positioning
Tool Shows citation context Why analysis Debate causality Gap detection Living updates
Scite ✓ ✗ ✗ ✗ ✗
Elicit ✓ ✗ ✗ ✗ ✗
Consensus ✓ ✗ ✗ ✗ ✗
ReviewOS ✓ ✓ ✓ ✓ ✓

The literature has all the answers.
You just need to know what question to ask.

ReviewOS turns millions of papers into a structured, honest picture of scientific knowledge — consensus, debate, and gaps — so your research starts where the field actually is, not where you assume it is.

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