AI_Business Hub

Who we are?_

A broad ecosystem, characterized by strong networks between science, economic actors and society to promote the best of AI for society and business development.

The AI Business Hub, intends to bring the theme of Artificial Intelligence and its applicability to the real world, contributing to prepare companies and society for this new reality. It is intended to promote the fusion of scientific knowledge and the best practices in the industry so that in a transversal way one can take the best advantage of this new technological revolution.

From the strategic vision to increase competitiveness to the choice and adaptation of the best solutions in each context, the ultimate goal is to encourage the implementation of practical and successful use cases, contributing to the modernization of companies, government and society.

In this sense, AI Business Hub will be an open space, technologically agnostic, fostering cooperation and sharing knowledge and experience. This is the biggest motivation of this initiative, which in the end, will belong to all who contribute to it in favour of a more competitive and modern society, but at the same time more inclusive.

Our Strategy_

We have designed our strategic approach within 4 complementary axles ilustrated below:

Sharing

Through use cases and best practices all the relevant knowledge to define corporate strategies.

Screening

The most adequate solutions to fulfil specific needs according to a predefined strategy

Fitting

Testing, and proofing the chosen solutions, minimizing implementing risks

Upskilling

All organizational levels with competences to deal with AI

Sharing

Knowledge & Strategy

Cross sectors

Board Level

Prooven Cases
Best Practices
Main Goals

Screening

Solutions Matching

Sectorial

C-level

Choosing & Adapting
Practical Workshops

Fitting

Paradigms Breaking

Intra company

Tech Level

Testing & Proofing
100 % Hands-on
Deep Dive

Upskilling

Competences & Resources

Focused

All levels

Intensive
Multi Disciplinary Approach

Initiatives_

Webinar

Do you want to be part of this Hub?

Talk to us

AI by sectors of activity_

Health

The health care industry deals with a variety of data which can be classified into technical data, financial data, patient information, drug information and legal rules. All this data needs to be analyzed in a coordinated manner to produce insights that will save cost both for the health care provider and care receiver while remaining legally compliant.

Insurance

From health to auto insurance, patterns can be clustered to better risk insurance management. Complex internal and external data could be processed using AI algorithms to forecast events probabilities to manage the insurance industry competitively.

Financial

The financial risk involving loans and credits are better analyzed by using the customer's past spending habits, past defaults, other financial commitments, and many socio-economic indicators. These data are gathered from various sources in different formats. Organizing them together and getting insight into customers profile needs the help of Data Science. The outcome is minimizing loss for the financial organization by avoiding bad debt.

Energy

As the demand for energy consumption soars, the energy-producing companies need to manage the various phases of energy production and distribution more efficiently. This involves optimizing the production methods, the storage and distribution mechanisms as well as studying the customer's consumption patterns. Linking the data from all these sources and deriving insight seems a daunting task. This is made easier by using the tools of data science. Data collection via IoT is trendy for real analysis.

(A)IoT

Real-time collection of sensor data and its analysis on the IoT platform can identify patterns and behaviours, Feedback received serves to identify the needed measures to adopt in advance, minimizing a vast category of problems in many sectors from health to city management.

Industry

The advancement in recognizing an image by a computer involves processing large sets of image data from multiple objects of the same category. For example, beyond face recognition, computer vision could be used to detect and prevent equipment failures on large industrial facilities

Telecommunications and Information Tecnologies

AI is playing a determinant role on the Natural Language Processing, allowing better and better systems for voice recognition, translation, sentiment analysis and correlated applications. Empathy simulation and, irony are examples within the most recent advances in this field to improve overall Customer experience in Telecom.