The AI co-scientist,
accelerating your research.
By the lab that built Virtuous Machines: Towards Artificial General Science→
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Trusted by researchers at
From the people who shape science.
I've found this to be the best for identifying statistical and methodological issues.
A remarkable review of a complicated paper, especially noteworthy for the depth of the methodological comments. I do not often see reviews by statisticians that are as detailed.
I've tried other AI tools aimed at improving science, but this was my first experience with something like this, and it feels truly different… it actually challenges you and helps you grow as a scientist.
90%of our users rate the outputs as equal to or better than human peers.
An evaluation for science.
Most quality signals arrive too late to act on, but the Calibre score doesn't. A 0-100 number broken down by where the work is strong and where it needs revision. So you have the specifics to improve, and see the weak points before a reviewer does.
What a Calibre score measures.
Alignment of design and question.
How well your study's approach can actually answer the question it sets out to ask.
Statistical and analytical soundness.
How well the analytical work behind your results - statistics, models, reasoning - holds up.
Conclusions sized to the evidence.
How well your claims are matched to the data behind them, measured against the standards of your field.
Could reach 96
Three unique elements.
A mixture of models, better than any one.
Every frontier model orchestrated: Claude, GPT, Gemini, Mistral, Grok, alongside our Explorer One model. Single-model bias removed by design.
An in-house science stack, scaling discovery.
The scientific method, automated with durable memory, verification at the source, and drawing from external data, not an LLM talking to itself.
Scientific agents that think like the field.
Enhanced with principles from human cognition to reason and act like scientists do. Specialised with tools, dynamically constructed to meet task complexity. Built and proven to do science.
The architecture underlying our tools runs science autonomously.See research →
Free isn't a trial, it's a tier.
Your first project is on us: a full review, then keep refining it with Rosa. Upgrade to take on more projects and tools: Researcher from $99/mo, Pro $199/mo, Institution by conversation.
FAQ
How is this different from running my paper through ChatGPT or Claude?
General-purpose LLMs read your work in a single pass using whatever knowledge they happen to have up to their training cut-off. They don't look up the current literature. They don't verify references. They don't score against field-specific standards. They don't check their own work. They can’t overcome their own biases.
Explore Science does all of these things, across a multi-phase architecture developed for autonomous scientific research. We orchestrate every frontier model (Claude, GPT, Gemini, Mistral, Grok) alongside our Explorer One model, and route each sub-task to the model that performs best on it. We verify every citation live to a DOI. We hold your manuscript in context across hours of analysis, not a single two-minute pass. That depth is the difference, visible in the nuance and insight of the feedback we give.
What models does Explore Science use?
A mixture, chosen by the system on a task-by-task basis. Different models perform better at different sub-tasks, in different reviewer roles, across different scientific fields, and the orchestrator routes each step to the model best suited for it.
The current mixture includes (but is not limited to) Claude, ChatGPT, Gemini, Mistral, and Grok, alongside our in-house Explorer One model. You don't pick a model; you get the strongest answer at every step - a consensus across models that cross-checks and removes single-model bias.
Is my manuscript used to train AI models?
No. We don't train models on user manuscripts - your work is yours.
Is it actually better than human peer review?
90% of users rank Explore Science's output as equal to or better than human peer review.
What we'll add is this: human peer review is unpaid, often rushed, and at times done by reviewers who may not be specialists in your exact topic. Explore Science brings consistent rigour, subject-matter depth, and a genuinely careful read to every submission - turning detailed feedback around in hours rather than months.
The goal is to make sure the version of your paper that reaches a human reviewer is the strongest one you can send.