Machine Learning: top European startups

Machine Learning is a new technology that is growing rapidly all over the world, including in Europe. Discover the top of the most interesting European machine learning startups.

Using the data, the artificial intelligence algorithms are able to to improve and learn without human intervention. It’s the Learning Machine.

This revolutionary technology has the power to disrupt all sectors and industriesand many dedicated startups have already been founded. Without further ado, discover the top of the most innovative and interesting European Machine Learning startups.

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Founded in 2016, is an artificial intelligence capable of Fulfill the role of marketing analyst. It allows mobile application marketers to focus on their priorities. Thanks to Machine Learning, this AI is able to analyze marketing campaign data and offer one-click optimization to proactively make changes. As a result, it is possible to increase ROI and simplify reporting.

Since its founding, the startup has raised a total of $2.4 million in two rounds. Its most recent fund raising was in November 2018, and was led by Partech alongside Sophia Bendz and Nicolas Pinto. was founded by Marie Outtier who worked 8 years in the ad tech field, and PJ Camillieri who worked 10 years at Apple.

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Auquan, a crowdsourcing platform for trading strategies

The platform Auquan enables crowdsourcing of data-driven trading strategies from a community of Data Scientists, developers, and Machine Learning engineers. It proposes to restructure trading in the form of data and mathematical problems.

Thus, everyone is able to discover patterns and create models using historical data without the need for financial experience. This startup was founded by a former Optiver trader named Chandini Jain and his Shub, a software engineer who previously worked for Gusto and Microsoft.

Causalens, the Machine Learning for predictive analysis

The startup of Machine Learning Causalens offers its customers to perform predictions from time-series data. Users are able to create dynamic predictive models at scale for complex, dynamic systems that are continuously changing. Based in London, Causalens was founded in 2016 by Darko Matovski and Max Sipos.

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CBAS, a neural engineering startup

Based in Cambridge, CBAS is a startup dedicated to neural engineering. It has created an open standard software and hardware interface between the human nervous system and the healthcare devices of the future. Its first product is the “Prosthetic Interface Device” (PID) which acts as a “USB connector for the body”. It connects to the limbs of the body via direct implantation in the bones and an electronic connection to the nerves.

CBAS claims to have collected the world’s largest neural data setfrom his clinical trials. These data allow him to conduct research in Machine Learning. Based in Cambridge, the startup was founded in 2015 by Emil Hewage (CEO) and Oliver Armitage (CSO).

Dogtooth, the Learning Machine for Fruit Harvesting

Founded in 2015 in Cambridge, the startup Dogtooth uses Machine Learning and robotics to harvest fruits and berries. Thanks to to computer visionThis startup allows robots to pick fruit with the precision, agility and speed of a human worker. In the future, the company plans to adapt its technology to a multitude of different use cases.

Grakn enables data analysis from dispersed sources

Grakn is developing a platform that allows companies to obtain information from dispersed data sources…but interconnected. Using the knowledge base, users can easily perform queries and data analysis.

The data are stored in a high-performance hyper-relational database on which a reasoning engine is run to check the relationships between data. Based in London and founded in 2015 by Haikal Pribadi, the startup raised $4.7 million in 2017 and received the Product of the Year award from Cambridge University’s Computer Lab.

GTN, the Learning Machine for Drug Discovery

Founded in 2017, GTN is a startup dedicated to drug discovery. With its patented Generative Tensorial Networks technology, it is able to search through the myriad of existing molecules to create drugs faster and less expensively. In May 2018, this European startup raised 2.1 billion pounds.

Hazy, the “RGPD ready” Machine Learning for data analysis

Hazy is a startup that helps companies to identify and anonymize personal data within large datasets while maintaining their usefulness. The objective? To enable customers to comply with the DPMR while enjoying the benefits of personal data.

Thanks to the Machine Learning, Hazy detects trends, patterns and correlations within a single, compressed data model. This model is used to generate synthetic data that keeps statistics and actual data values in a completely confidential form.

Kheiron Medical, the Breast Cancer Learning Machine

Founded in 2016 by Peter Kecskemethy and Tobias Rijken, Kheiron Medical seeks to fight breast cancer thanks to the Machine Learning. Specifically, the startup’s software helps radiologists by enabling them to detect malignant cancers on X-rays more effectively.

Latent Logic makes robots more human thanks to Machine Learning

The start-up Latent Logic, founded in 2017 in Oxford, has developed Machine Learning techniques to help people learn how to use the Internet. allowing robots to perform complex tasks usually reserved for humans by learning from a demonstration.

Its technology is initially intended for autonomous vehicles.. In this field, the startup makes it possible to accelerate the development of autonomous control systems or to test performance and safety through simulations with realistic human behaviour.

Mapillary creates street views from crowdsourced photos

Using a simple smartphone or GoPro camera, anyone can now take pictures of the streets they visit. Swedish startup Mapillary, founded in 2013, offers a computer vision platform that allows you to combine these photos automatically to create street views. such as those offered by Google.

For privacy reasons, faces and license plates in photos are automatically blurred. Since its foundation, Mapillary has raised $24.5 million with investors such as Sequoia, Atomico and BMW i Ventures.

nPlan solves the problem of construction site delays with Machine Learning

The nPlan startup, founded in 2017, is using the Deep Learning to solve the problems that cause delays in major construction projects. Its Machine Learning algorithms understand the performance of a project in relation to context, and learn from the results of previous projects.

This allows them to identify the risks of project delaysand recommend improvements. Its level of accuracy exceeds all existing solutions. The objective of this startup is to enable owners, insurers, investors and governments to better plan their projects.

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