In order to provide you with solutions for diagnosis, prediction, monitoring, optimisation or forensic analysis, BABEL has multidisciplinary teams that combine skills and experience in artificial intelligence with the adjoining technologies and capabilities necessary to turn these solutions into tangible results.

Knowledge and experiences at corporate level of machine-learning algorithms and the use of tools to do so is not enough. Software architectures must be provided that facilitate the incorporation of data from its source into the expert system, sometimes responding to real-time requirements or complex processing of large volumes of data. Complementation with our specialised lines of big data, BI, IoT or integration architectures is a mainstay of our artificial intelligence strategy.

Software architects and engineers, data scientists and business experts combined with proprietary tools built during previous projects, along with technologies and resources from industry and the scientific community, such as the Python ecosystem with Scikit Learn, Kera, Theano or TensorFlow, the defining of Mlops architectures or even Machine-Learning Automation tools act as the basis for our strategic position in offering professional services and machine-learning solutions.

Through the use of machine-learning algorithms, and the platforms and tools in which we have specialised to use them, we help obtain the knowledge that the data encloses.

Most organisations now have large volumes of data for which their managers sense the value and knowledge contained.

From the ability to discover the simplest methods of unsupervised classification, to the combined use of algorithms from different groups of classification, optimisation or neural networks, we provide diagnostic solutions, finding patterns of accumulated information, and using our capabilities in big data and analytics.

BABEL provides our clients with the knowledge and ability to design, develop and industrialise their machine-learning activity.

The need to transmit, intake, process and analyse data has become an essential tool for companies that need to extract information and operational intelligence in increasingly large volumes of data. When this need is combined with immediacy, there is a need to be able to analyse events that move and vary at high speed (market information, mobile devices, sensors, etc.).

Telecommunications event analysis, predictive maintenance, fraud detection and prevention are just some of the examples in which we help our clients be extraordinarily competitive in an extremely dynamic market.

Many artificial intelligence projects require the specific scaling up of computational resources, the costs of which might offset the profits provided by the project. In addition to the hardware platform, cloud services from the main providers include execution environments for artificial intelligence algorithms, scaling up resources whenever they are needed.

We are involved in one of the most cross-cutting and multidisciplinary challenges to have arisen in recent years.

The mainstays of Industry 4.0 are based on IoT, cyber-physical systems and automation and robotics; additive manufacturing, smart material technologies and advanced maintenance; modelling, virtualisation and simulation of processes, safety & security and human-machine interaction and big data, data analytics and cloud.

Success stories accumulated over recent years on many of the above mainstays, along with our focus and the specialisation of our line of artificial intelligence services, represent our strategic positioning in Industry 4.0, where our pattern-setting or optimisation efforts find vehicles for interaction with the physical world.