Digital transformation

Why digital transformation?

The adoption of cloud computing and emerging technologies associated with the cloud allows us to address improvements and innovation in all areas of management:

How we interact better with clients, how we manage a company with more accurate statistics, how we better associate, how we shape more productive employees.
And even, in some cases, how do we reinvent our business model?

What does working in the cloud bring to companies?

New more modern ways of working that give you the agility and competitiveness that your business needs.

More mobility and accessibility to your files

From anywhere and using any device

Business intelligence

to be able to successfully meet any business challenge

Flexible storage and more security

Constant innovation

thanks to Google, with constant updates and new management tools, communication and cloud computing.

Agility and cost savings

Goodbye to hardware and software, to installations and updates. In the cloud, resources are flexible and tailored to each business.

Explore big data, compilation and classification

of the data generated to gain efficiency and productivity.

More communication with your teams and your network

allow your teams to be connected and under the new paradigm of online collaborative work.

Machine learning

for constant improvement of our processes and activities

In short, new more modern ways of working that give you the agility and competitiveness that your business needs


José Luis Cerrada | CTO

These are very special times that we are living in. Cloud Computing allows us to implement applications in record time and perform tasks that used to take us a long time in a few seconds.

In addition to this speed, we can pay flexibly for the use we give to technology. And we can delegate all the infrastructure to a third party, for us to dedicate ourselves to what we really know how to do well: our business.

Discover the reach of new technologies


Today’s applications generate a variety of data sources within the company, extending to the physical world where any device is able to capture important signals for analysis.

All these data relevant to the business can be processed efficiently and on a large scale, through the integrated Big Data platform of Google Cloud Platform, enabling predictive analysis and providing valuable information in areas such as operations, marketing and sales.

Cloud Platform offers us an end-to-end, proven and integrated Big Data solution, based on years of innovation in Google, which allows you to capture, process, store and analyse all the data generated in a single platform.

Do you want to know what the areas of application of Big Data in your business are?

Contact us and we will be happy to help you.

IOT (Internet the las cosas)

The Internet of Things is essentially a system of machines and objects equipped with data collection technologies, enabling those objects to communicate with each other. The data that are generated have a lot of uses, but they are often used to determine the health and state of things.

The objective is to make all these devices or objects act more intelligently and independently, connecting to the internet and each other, exchanging data with external servers and acting according to the information collected, both from sensors and servers.

For this purpose, it is necessary to use the IPv6 protocol and the development of numerous technologies that are currently being designed by the major companies in the sector.

Google has the Google Cloud IoT Core, a service designed to help securely connect and manage large-scale devices. Numerous companies in various sectors such as transport, oil, public services and healthcare are already using this service.



Machine Learning is a branch within the field of Artificial Intelligence whose goal is to give computers the ability to learn autonomously and automate, through different algorithms, the identification of patterns and trends from the data.

Machine learning algorithms are often classified as supervised or unsupervised. The supervised algorithms work with “tagged” data and learn from a data history to predict a certain output value.

A simple example would be Google’s SPAM, where a classification problem is applied, such as the detection of junk mail or spam.

In the unsupervised algorithms, no previous experience is available. Therefore, it is mainly aimed at discovering implicit relationships and patterns in a data set without prior labelling, as is the case of scientific analysis, which is clearly exploratory.

Not only the choice of the most suitable algorithm is very important but also the fact of having a large volume of data of sufficient quality.

Once the objective and the information that we must collect are defined, Machine Learning can be enormously useful when it comes to detecting tendencies and behaviours. And in this way, to make predictions and facilitate decision-making in all functional areas of the company.

In this process, the role of the technology consultant is fundamental since they can guide your company from the concept to implementation, through a wide range of packages and services that focus on developing machine learning solutions.

Do you want to know about our real cases of Machine Learning?

Contact us and we will be happy to help you.