[FW Radar] CyberValue wants to detect anomalies that slow down the growth of a business

by bold-lichterman

Launched in 2017 by Guillaume Leboucher, CyberValue relies on artificial intelligence and Big Data algorithms to detect anomalies in a company.

More details with Guillaume Leboucher, the founder of CyberValue.

FrenchWeb: What needs does your service meet?

FW Radar CyberValue wants to detect anomalies that slow downGuillaume Leboucher, the founder of CyberValue: CyberValue is an anomaly detection platform. It allows companies to detect proactively has themNetwork attacks, maintenance problems, abusive expense reports, false declarations,… in short, the various problems which slow down their growth. By relying on intelligence artificial and the latest big data technologies, CyberValue enhances the data of any company to extract value and achieve substantial savings. So the companies can protect themselves, anticipate and optimize their internal resources.

What is your value proposition?

CyberValue has developed one of the first new generation multi-sector anomaly detection solutions created in France. It offers a new approach, which is based on 3 pillars: Artificial Intelligence, behavioral analysis and real-time processing. It is about offering a simple, scalable, adaptable and efficient solution in all circumstances. To meet this challenge, the solution relies on full mastery of machine learning and deep learning, as well as on the latest Big Data technologies.

Who are the users of your solutions?

Many sectors of activity are concerned (insurance, mutuals, IoT, e-commerce, etc.) but more generally the users of the solution are operational managers who experience anomalies or malicious acts within their processes internally or externally. (anti-fraud cells, maintenance center, management controller, etc.).

The solution allows them to relieve themselves of a technical part that is often far removed from their skills. Our tool allows the “analysis” teams to refocus on the value-added tasks of investigating and processing alerts detected by the solution. The solution is self-learning and issues more and more relevant alerts over time.

What is your development plan?

Our start-up aims to become the first quantum anomaly detection solution. This shift towards a new paradigm must make it possible to process ever more data in real time, with even more complex algorithms in order to detect the most subtle and complex patterns.

What are your challenges?

The main challenge is to be audible in front of interlocutors who are often not very specialized in the technologies used. We must succeed in simultaneously promoting the simplicity of the solution and its capabilities thanks to the complexity of its algorithms.

Who are your competitors?

We have competitors specializing in the detection of malicious acts, and even sector competitors (banking, insurance, etc.). While some solutions offer artificial intelligence algorithms, many are based on outdated analytical techniques.

Our start-up aims to offer the first multi-sectoral solution capable of handling all use cases, thanks to the power of machine learning and deep learning.

Key data:

  • Founder: Guillaume Leboucher
  • Creation date : 2017
  • Fundraising : 1.5 million euros with Venture Capitalist America
  • Seat : Paris