AI that thinks
like a scientist

BioSkepsis is an AI research assistant for life sciences that turns a single research question into a fully worked, evidence-backed answer.

Used by scientists across academia and industry.

University of CambridgeKing's College LondonUniversity of MarylandUniversity of YorkUniversidad Complutense de MadridNational and Kapodistrian University of AthensUniversity of CyprusFORTH IMBBUniversity of IoanninaCyprus University of TechnologyChrist UniversityEuropean University CyprusCyprus Institute of Neurology & GeneticsUniversity of CambridgeKing's College LondonUniversity of MarylandUniversity of YorkUniversidad Complutense de MadridNational and Kapodistrian University of AthensUniversity of CyprusFORTH IMBBUniversity of IoanninaCyprus University of TechnologyChrist UniversityEuropean University CyprusCyprus Institute of Neurology & Genetics
DW
Debbie Winters

Cancer Medicine

BioSkepsis is genuinely impressive. With tools like ChatGPT or Copilot, you still have to search for papers yourself and feed the information in. BioSkepsis does that entire process automatically — it finds the studies, extracts the evidence, and provides the citations so you know the information is reliable. I’d be silly not to use BioSkepsis to help write my thesis.
MP
Michalis Paraskeva

Applied Genetics and Biodiagnostics

BioSkepsis helped me move beyond simply finding papers and allowed me to explore an entire research field in a structured way. The Research Landscape feature was particularly valuable for identifying key themes, emerging trends, and knowledge gaps. As a researcher working in microbiology and bacteriophage biology, I found it to be a powerful tool for literature exploration and research synthesis.
KK
Konstantinos Kounakis, PhD

University of Crete / IMBB-FORTH

I’ve been using BioSkepsis for over six months now: for searching methods and tools for the experiments I’m planning, for finding papers relevant to the manuscripts I’m writing, and for keeping up with newly published literature in my fields of interest. Over this time I’ve seen it evolve into a potent assistant that has saved me dozens of hours of effort. BioSkepsis is great at parsing and extracting information from the literature, as well as identifying semantic relations between papers. In regards to biomedicine, it surpasses general-purpose LLMs and even some dedicated scientific LLMs, and it has the potential to match the top competitors in this field.
SB
Sarah Emily Bahari

AuDHD Medical Biotechnology Student

As a Medical Biotechnology student, I spend a lot of time navigating scientific papers and trying to make sense of complex research topics. BioSkepsis made that process more efficient by helping me find relevant literature, understand biological mechanisms, and trace information back to its original sources. I particularly appreciate its focus on evidence-based outputs and citation transparency.
MT
Muhammad Talha

Chemistry Teacher & Trainer, Co-Author of an A-Level Chemistry Book

One thing I would love to appreciate about bioskepsis is that it can make life easy for a research student who has to go through hundreds of articles and research papers and couldn’t get the relevant information out of it. What bioskepsis has done is that it gives us all the relevant information from the relevant papers and you can make excellent progress as a researcher without checking every article that comes in your way but you can select the most relevant ones and can go deep in your own research to compare it with.
MS
Marilia Soteriou

Pharmacy Student

I genuinely enjoyed using BioSkepsis. I found it really helpful, especially for quickly understanding scientific papers and saving time during research. The interface is clean and easy to use, which makes the whole experience much smoother. I honestly think it has a lot of potential, and I can’t wait to keep using it.

Swipe for more

How it works

Built like a careful researcher

BioSkepsis is an agentic AI that runs the entire research workflow for you: it plans your question, searches and reads the literature, weighs the evidence, screens for reliability, and synthesizes a cited, verifiable brief.

BioSkepsis

Plans the question

Breaks your question into focused sub-questions, then works through each one.

Curated search

Searches broad life-science literature, then weights top-tier, authoritative sources.

Full-text reading

Reads entire papers, not just abstracts, to capture methods and context.

Evidence weighing

Types each finding and weighs supporting against contradictory evidence, surfacing contradictions and gaps.

Trust & safety

Blocks retracted and hijacked-journal sources, and flags corrections.

Cited brief

Verifies every claim against full text, then synthesizes a brief with a Trust Index.

Beyond keywords

Reads the full story, not just the abstract

  • Reads full text content
  • Finds foundational papers
  • Cross-checks key findings
  • Screens retracted & corrected papers

TGF-β signaling in cancer cachexia

Journal of Cachexia, Sarcopenia and Muscle · 2016

Full text

Read in full

AbstractIntroductionMethodsResultsDiscussion

Key findings extracted

Foundational papers

Most co-cited by your sources
  • Smith et al. 2016Foundational study
  • Jones et al. 2014
  • Lee et al. 2018
No retractions1 correction flagged

Literature landscape

Map the full biologySee the real connections

We reduce each paper to the biology it actually discusses (genes, proteins, drugs, diseases, pathways, GO and MeSH terms) and connect papers whose biological fingerprints overlap.

A literature landscape map with seven colour-coded research communities (IL-6/JAK-STAT signaling, TME and myeloid modulation, biomarkers and prognosis, combination strategies, chemoresistance mechanisms, preclinical models, and clinical evidence and trials), each shown as a cluster of connected paper nodes.

Distinctive concepts count more

Connections are weighted by distinctive shared concepts, so closeness reflects topical similarity, not citation habits.

Themes, anchors, bridges

Community detection reveals research themes, anchor papers, and the bridges that link them, plus whether each theme is rising or fading.

Built by the agent

The agent builds the map from curated, full-text sources and weaves it, citation-verified, into your brief.

Evidence you can trust

Every claim is cited, verified, and evidence-typed

Each finding is checked against the source's full text and tagged by evidence type, and every brief gets a Trust Index.

A BioSkepsis brief showing a Trust Index of 82 out of 100, six trust facets, and a table of claims tagged by evidence type with verified citations.
  • Types every finding by evidence strength
  • Verifies citations against full text
  • Scores each brief on a six-facet Trust Index
  • Flags claims backed by multiple sources

From insight to impact

From conclusions to next steps

Generate testable hypotheses and experiment designs, so you leave with a plan, not just a summary.

  • H1

    IL-6 blockade will reduce muscle wasting in pancreatic cancer by modulating STAT3 signaling.

  • H2

    IL-6-driven cachexia is mediated via myeloid cell-derived factors.

  • H3

    Combination of IL-6 blockade + nutritional support improves survival vs. control.

Microscope and lab flasks