Software & Data

The software industry is overwhelmed by new business models, new distribution methods, open source, new production models, as well as the avalanche of data and AI.

Customers’ expectations are changing, and their demands are increasing in an increasingly international competition. The consumption of services is now quantitative, by users who want to be more and more “data-driven”. Simultaneously, data and the democratization of Machine Learning allows the creation of new strategic functionalities for the user, thus rewriting the maps of the competitive landscape.

The upheaval caused by new customer expectations is accompanied by major changes in software production. As agile development and continuous deployment become the norm, the software must now adapt its structure by porting it online through the cloud and adopt a more flexible business model than the traditional license, ranging from subscription (“SaaS”) to Freemium.

This dual transformation of software and production suddenly puts a strain on labor markets around the 3 new technical challenges: capturing, organizing and exploiting data. Software publishers then must make significant recruitment efforts in an international talent war.

The scale of these changes and their implications for the individual  provoke a new economic tension, forcing institutions to mobilize to defend the interests of their region. Europe is leading the privacy protection policy with the adoption in 2018 of the GDPR (General Data Protection Regulation), while China is pursuing a more central and national policy towards this new virtual gold. These regulations are additional constraints for software publishers.

Key technological enablers

Deep learning

Deep Learning uses machine learning in successive layers, allowing engineering features to be automated; it relies heavily on neural networks. New algorithms, access to large computing capabilities and the multiplication of the amount of usable data enabled radical progress in areas previously reserved for humans, such as vision and language.

Sensors & MeMS

Microelectronics has led to fundamental advances in sensors and actuators. More compact sensors (nanotechnology), less expensive, with embedded intelligence, with more autonomy and sometimes self-sufficient in energy, allows more precise control of assets, production lines or the operation of complex systems.

Augmented Reality

Augmented reality (AR) adds virtual elements (indications, clothing, furniture…) to the real environment. Advances in image recognition and digital modeling not only allow the emergence of new and enhanced customer experiences, but also the assistance of any field operator in real time.


The Cloud brings together all the technologies that allow remote data storage and processing, often on shared solutions. The pooling of material costs and the development of platforms give any company access to flexible, high-performance, secure and cost-effective IT infrastructures and services.

Machine Learning

Machine Learning brings together all the technologies needed to automatically calibrate a model to make it more reliable. The improvement of computing power and the increase in the amount of usable data allows computers to automatically adjust their predictions and behaviors, and the development of more accurate and efficient predictive and decision-making algorithms.

New Coverage Technologies

The multiplication of networks (cellular, satellite, mesh, etc.) with extended coverage allows the deployment of projects based on continuous data collection and transfer, both locally and internationally.

Examples of eleven’s support in the industry