Solutions that go beyond Business Intelligence
Discover our tools with AI & Data Science engines and Machine Learning methodologies to optimize your business practices starting today.
AI & Data Science engines powered by BIsiona technology
At BISIONA, we understand that in an increasingly competitive environment, innovative solutions powered with AI & Data Science methodologies are needed. Not only answering to market demands but also proactively anticipate them.
That’s why, since 2019, we have been working on AI & Data Science technologies in collaboration with the Polytechnic University of Madrid. Together, we have developed innovative methodologies and solutions applied to business cases in the pharmaceutical and healthcare industries.
As a result of this collaboration, we offer proven value models based on Machine Learning, AI, and Data Science, integrated into our “baia” module.
Advantages and benefits
The application of our Artificial Intelligence models helps solve common problems such as:
Active recommendations
Identifying success patterns in commercial activity translates into active recommendations for application in specific territories, improving sales results cycle by cycle and boosting commercial performance in each region.
Territorial alignment
Intelligent optimization of territorial alignment in sales networks through algorithms that generate ideal territory assignments.
These alignments aim to achieve various objectives, such as:
➥ Reducing the territorial structure without affecting sales volume.
➥ Increasing the potential sales volume, reallocating territories, and calculating the need for new salespeople.
➥ Optimally reorganizing the existing sales network.
➥ Creating a new territorial structure for product launches, among others.
Our intelligent AI assistant
Business Artificial Intelligence Angel “baia” is BISIONA’s new set of models and methodologies that integrates advanced AI and Data Science techniques.
By applying our AI engine, we aim to help businesses create more accurate commercial strategies and improve sales performance through the active and predictive recommendations generated by the system.
To achieve this, at BISIONA we have developed a set of analysis models and methodologies based on the application of various statistical Machine Learning methods and algorithms, which enable both the continuous and automated learning of behavior and the identification of success patterns.
This generates a unique and real differential value proposition for each of our clients.
The AI solutions we offer through “baia” are specific and tailored to each business, product, pathology, and objective. By integrating multiple data sources, all associated numerical and discrete variables, and analyzing the information, we predict success patterns that allow us to improve:
- Sales performance through the application of more precise recommendations.
- Company practices by predicting success patterns.
Additionally, because the system allows for the consideration of multiple scenarios, we can select the one most suited to our needs.
To achieve this, “baia” enables the generation of simulations by considering various factors and variables, with the option to incorporate any type of assignment restrictions.
This makes the model a flexible, scalable, and adaptable solution for any scenario.
By applying our AI engine, we aim to help businesses create more accurate commercial strategies and improve sales performance through the active and predictive recommendations generated by the system.
To achieve this, at BISIONA we have developed a set of analysis models and methodologies based on the application of various statistical Machine Learning methods and algorithms, which enable both the continuous and automated learning of behavior and the identification of success patterns.
This generates a unique and real differential value proposition for each of our clients.
The AI solutions we offer through “baia” are specific and tailored to each business, product, pathology, and objective. By integrating multiple data sources, all associated numerical and discrete variables, and analyzing the information, we predict success patterns that allow us to improve:
- Sales performance through the application of more precise recommendations.
- Company practices by predicting success patterns.
Additionally, because the system allows for the consideration of multiple scenarios, we can select the one most suited to our needs.
To achieve this, “baia” enables the generation of simulations by considering various factors and variables, with the option to incorporate any type of assignment restrictions.
This makes the model a flexible, scalable, and adaptable solution for any scenario.
This project has been co-financed by the European Regional Development Fund (ERDF) and the Center for Industrial Technological Development (CDTI), with the aim of promoting technological development, innovation and quality research.
BISIONA BUSINESS SOLUTIONS, S.L.
‘RESEARCH AND DEVELOPMENT OF NEW ARTIFICIAL INTELLIGENCE TECHNIQUES FOR COMMERCIAL EFFECTIVENESS IN THE PHARMACEUTICAL INDUSTRY’ (IDI-20211219)
A WAY OF MAKING EUROPE
The objective of this project (12/2020-03/2022), located in Madrid, with a budget of €326,829, has focused on the development of a predictive system that proposes actions to the commercial network of pharmaceutical laboratories and medical devices. best suited to improve their performance. An original methodology based on Artificial Intelligence (AI) techniques has been researched and developed that repeatedly offers recommendations to each component of the commercial network based on the analysis of a wide set of variables.
Thanks to this research, Bisiona has undertaken the experimental development of a prototype of an Intelligent Decision Support System (SIAD) for commercial efficiency in the pharmaceutical sector that acts as a centralizing element that helps commercial efficiency. Based on the predictions obtained from the analysis of the different variables in the instances, the system will propose different actions related to the dissemination of content, execution of action plans, their adaptation, optimization of routes and visit plans. and other actions derived from the analysis of indicators and the predictions provided by the solution.
