Use cases


Explainable AI Platform

1 • Life and health sciences

Division of AyGLOO wholly dedicated to Life Sciences and Healthcare

Get all of the value from artificial intelligence to make the best decisions.



Diagnostic processes, treatment and disease prevention.



Pharmacology and Biotech

Drug development.


Digital Twins.

Salud y deporte


Prevention of muscle injuries.


Food Science

Development of new foods.

INDIA – Explainable AI platform with business intelligence for the healthcare and life sciences industries

Biotech or pharma:

Drastically reduces the time-to-market and development costs of a drug, molecule, product or vaccine when using AI/ML models.


Greatly improves a medical practitioner’s confidence and decision-making when using ML/IA to diagnose, treat or prevent disease.

All cases:

Huge reduction in the complexity of the process because it allows a researcher or doctor to understand how the AI decides and works directly with the data without programming and without the need for any statistical knowledge.

Complete analysis process controlled by the researcher, analyst or technician.

  • It is presented through an intuitive and interactive dashboard.
  • Allows the selection of variables either from the model, external or proposed by the platform to mimic the original model in as many easy-to-understand models as the researcher wishes, which provides a lot of valuable information on how the model decides.
  • Identifies biases, flaws and hidden relationships between variables from a global perspective, in critical segments and on a case-by-case basis.
  • Includes what-if analysis and counterfactuals to draw valuable conclusions about unusual behavior, decision thresholds, minimal changes for the model to make different decisions, etc.

Helps the technician to refine the model during its development and once in production with ROC analysis graphs, residuals, etc.

INDIA has been validated for the pharmaceutical sector

INDIA is a secure platform for your sensitive data which complies with GDPR in terms of security and governance of data.

INDIA complies with the principles of ethical and responsible AI.

INDIA – Explainable AI Platform for Natural Language

Explainability analysis of<br />
medical text document<br />
XAI_Computer Vision

INDIA – Explainable AI Platform for Computer Vision

Member of

Barcelona Health Hub-logo-gris

Member of the BCN Health Hub

Since October 2022.

The mission of the Barcelona Health Hub association is to boost innovation in digital health and its transfer to the sector, linking startups, health organisations, businesses and investors.

healthcare infographic

2 • Other processes

Energía y Fabricación

2.1 • Critical processes

If AI is used for decision making and your business process is important to your business, AyGLOO gives you a unique AI tool to make fast, accurate and confident decisions:



An executive is going to be able to analysis directly with the data to understand in which segments the algorithm is not working correctly and how the model would decide with user own variables that have not been taken into account in the construction of the algorithm.


An executive will easily understand what changes can be made so that the algorithm can make different decisions and optimize decisions.


A technician will easily understand why the algorithm allows some accesses that it should not or vice versa.


They use AI at the core of the business and not understanding how the algorithm decides can lead to fatal errors. An executive will be able to guarantee in a simple way that the algorithm is optimized and does not have anomalous results in customer segments or include variables in the analysis that are not in the original model to obtain valuable business insights.

2.2 • Responsible processes

If you use AI in processes that make decisions about people, AyGLOO provides you with a tool to ensure transparency and accountability in the use of AI. In an intuitive way you will be able to, for example:



A bank executive can do simple analysis with the data to understand the reason why the AI denies granting a credit to a customer and recommend some changes to grant the credit.


An executive who selects personnel can do simple analysis to understand why the algorithm he uses does not select a certain profile, for example women over 40 years old.


An actuary will be able to do intuitive analysis to see if the algorithm is biased and making wrong decisions in calculating the price of the policy for a user or group of users.

Energía y Fabricación