Use cases
INDIA
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.
Healthcare
Diagnostic processes, treatment and disease prevention.
Devices.
Pharmacology and Biotech
Drug development.
Pharmacovigilance.
Digital Twins.
Sport
Prevention of muscle injuries.
Food Science
INDIA – Explainable AI platform with business intelligence for the healthcare and life sciences industries
Biotech or pharma:
Health:
All cases:
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 – Explainable AI Platform for Natural Language
INDIA – Explainable AI Platform for Computer Vision
Member of
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.
2 • Other processes
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:
SOME CASES:
FRAUD DETECTION:
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.
PREDICTIVE MAINTENANCE:
An executive will easily understand what changes can be made so that the algorithm can make different decisions and optimize decisions.
CYBERSECURITY:
A technician will easily understand why the algorithm allows some accesses that it should not or vice versa.
NATIVE DIGITAL COMPANIES:
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:
SOME CASES:
BANK:
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.
PERSONNEL SELECTION:
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.
INSURANCE:
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.
