We are a research focussed company taking on problems that are only possible to solve with machine learning and AI. We specialise in automating the repetitive task of data cleansing or "scrubbing". Spreadsheets are currently cleansed with rule based systems, normally written as Excel macros. These don't scale and can't take into account multiple edge cases in the data. We use the latest breakthroughs in Natural Language Processing (NLP) and Machine Vision to achieve above human accuracy in data cleansing.
Andrew has a Masters in Machine Learning from UCL and 4+ years of experience as a machine learning researcher and engineer. He has previously deployed big data machine learning solutions in several companies, including banks and law firms.
Alex is a full stack developer who contributes to major open-source Excel python libraries. He has UI, front-end, product management, and business strategy expertise with an MBA from the IE Business School, Madrid.
Nicola has 6+ years of experience in the insurance industry as a Lloyd's Property Underwriter and Catastrophe Modelling Assistant. She has first-hand experience of the delights of the day-to-day data cleaning tasks and workflows in insurance.
Pontus is an Associate Professor in Natural Language Processing at University College London (UCL), Head of the UCL NLP research group, and Deputy Directory of the UCL Centre for Artificial Intelligence. He has 10+ years of experience as a leading NLP researcher with more than 60 publications that have been cited more than 2,500 times and has served and currently serves as an advisor to several startups.
Data Scientist | Founding Team
Axel van Lith
ML Engineer | Founding Team
Mike has 6+ years of experience in data analytics, most recently as a Data Scientist at Facebook and Profitability Lead at Stuart Delivery. Mike excels at generating insights from data, building meaningful KPIs, and is a pandas/SQL wizard.
Axel has a Masters in Machine Learning from UCL where he focussed on NLP and worked with Pontus to implement an Anisotropic Hierarchical Vector Quantizer. Axel excels at generating augmented and synthetic data in order to boost the accuracy and robustness of large NLP transformer models.