Empowering people to check facts.

A state-of-the-art fact-checking system using machine intelligence.

Proudly backed by the Google Digital News Initiative.

Reducing online misinformation using artificial intelligence.

Factmata is built upon cutting-edge academic research in natural language processing and information retrieval. We are launching a state-of-the-art fact-checking system using machine intelligence, for statistical claims made in digital media content, such as news articles and political speech transcripts.

Our first goal is to make fact-checking more automated, more fun and easier. We want to build a product that engages people in the process of correcting news articles, identifying fallible claims, and supporting more accurate information on the web.

We hope to apply state of the art artificial intelligence to broader misinformation problems that exist on the web. This includes automated systems for detecting fake news, tracking rumours and hoaxes, tracking promises and many more. We believe that misinformation leads to mistrust, and this leads to broader social and political problems.

Our mission is to protect people from misleading information they are exposed to on a daily basis, and empower them to not take anything for granted.

Our Team

We are a team of machine learning and natural language processing researchers.

Dhruv Ghulati

CEO and Research Scientist

Dhruv holds a Distinction in Computer Science and Machine Learning from University College London, and a 1st Class BSc in Economics from the LSE. He was a product manager and co-founder of two London based machine intelligence startups, and Entrepreneur First alum. He wrote his thesis in cost-sensitive classification and distant supervision for statistical claim detection.

Dr. Robert Stojnic

CTO and Head of Engineering

Robert has been at Wikipedia in the early days where he designed, implemented and managed the search on Wikipedia. After that he went on to apply machine learning to problems in biology and genomics, earning him a PhD at University of Cambridge in 2012. Since then he has been a post-doctoral researcher and CTO at GeneAdviser which developed software for the NHS.

Dr. Thiago Galery

Chief NLP Architect

Thiago holds a PhD in Computational Linguistics from UCL, and is an Natural Language Processing (NLP) engineer with 4+ years of academic experience and 5+ years of industry experience. He developed grammar sentiment analysis at IBM, semantic recommentation at Idio and named entity recognition for Signal Media. He is a consultant for one of the most reputed pieces of ML/NLP software, gensim, develops and maintains NLP services for CompyAdvantage’s apis, and contributes to the well-known open source Entity Linking system known as DBpedia Spotlight.

Rishabh Shukla

NLP Engineer

Rishabh has been the CTO at Neuron, a New Delhi based machine learning startup, and involved with research and development of Scalable Deep Learning Models for Natural Language Processing (NLP). He is an active open source contributor and Google Summer of Code Intern. He is interested in working with Generative Models and carrying out research work in the field of Natural Language Understanding (NLU), and holds a Bachelor in Technology (B.Tech) from SMVDU, Jammu.

Joshua Vantard

Head of Growth

Joshua studied for a BSc in Economics before completing a BA in Philosophy and MA in Philosophy at KU Leuven, Belgium, specialising in Risk and Technology. While participating in Leuven's Advanced MSc in Artificial Intelligence and Computer Science, Joshua joined. He crowdsourced fact-checks with hundreds of contributors and tens of thousands of views, used by journalists such as at the BBC and New York Times. He built a diverse range of large online and offline communities while at university.


Dr. Sebastian Riedel

Scientific Advisor

Sebastian is a Reader at University College London and leading the Machine Reading Lab. He is an Allen Distinguished Investigator, Marie Curie fellow and received a Google Focused Research award. Sebastian is generally interested in the intersection of Natural Language Processing and Machine Learning, and particularly interested in teaching machines to read and to reason with what was read. He has published various papers on this topic, covering questions related to scalable inference, probabilistic programming and representation learning.

Dr. Andreas Vlachos

Chief Research Scientist

Andreas is a lecturer at the University of Sheffield, working on the intersection of Natural Language Processing and Machine Learning. Current projects include natural language generation, automated fact-checking and imitation learning. He has also published research on semantic parsing, language modelling, information extraction, active learning, clustering and biomedical text mining.

Join us in our mission

We are hiring full stack engineers, UI designers and NLP engineers to help solve the problem of computational fact checking.

See Open Positions

Press and Media

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