Making the best decisions, identifying trends, recognising and failures, making use of accumulated information… So many actions which, in industrial fields, can be supported and accompanied by data analysis or by the algorithmic modelling of human expertise. How? With “data” expertise, which will provide you with personalised, reliable, and sustainable tools for assisted decision-making!
Of course, for decades industrial products, services and systems have been automated, robotised, and computerised on models that are already known. Although operational and functional actions are now often supported by computer programmes, the fact remains that decision-making often remains human with failures always possible. However, to adapt to the complexity of the problems encountered, we can now use data science technologies to seek out relevant information and make reliable decisions.
With the multiplied power of current computers and modern algorithmic possibilities, manufacturers now have the possibility of “canning the intelligence of experts”. In other words, to produce concrete knowledge, and above all, highly reliable assistance tools for their decision-making. Among the tailor-made interventions of the “data” expertise: simulators in hydroelectric energy, onboard systems in the automobile, predictive models in the energy field, alert systems in the agri-food sectors, etc.
You too can benefit from assisted decision-making tools derived from “data” expertise, using personalised solutions taking into account both the latest technological advances, “business” expertise and the possibilities revealed by use of your data. Based on mathematical models faithful to reality, we provide you with optimised decision support tools. These tools will give you access to new ways of optimising your systems!
In 2000, discussions about algorithms and models were restricted to experts. Since then, these terms have become common parlance, and new professions have made the headlines concerning a new field known to all as “Data Science”.
The principle of a neural network is to schematically reproduce the human brain and its way of associating items so as to automatise the process into a machine : it is commonly called artificial intelligence.
