Digitalization

Your partner in Digitalization

To become a company governed by data and Artificial Intelligence, the keyword is Digitalization.

We can accompany your strategic plan around data and Artificial Intelligence to make the most of the technologies, starting by building a solid foundation and progressing towards intensive use of AI in your processes.

01 Data, Sensing, and Integration

Example: computer vision systems for feed tracking or detection of lung pathologies.

Utilization of existing data in technical and economic applications.

Sensor Deployment for acquiring existing data (temperature, CO2, etc.) or improving the resolution of new data (individual traceability, time of a drop...).

Quality Integration To maintain unified data from multiple heterogeneous sources. Here, there is a significant challenge due to historical trajectory and lack of standards in the sector.

02 Monitoring and Alerts

Example 1: Traffic light system for feed based on its technical and economic results.

Example 2: Alert triggering and actuator activation based on temperature.

Digitalization and data integration allow us to achieve easy wins by defining indicators and alerts to keep production within known values.

03 Descriptive Analytics

Example: analysis of the interrelationship between temperature, altitude, humidity, diseases, and production values such as IC and GMD.

Rigorous application of mathematics and statistics to make sense of the data, analyze different variables, their relationships, and their contribution to our objectives.

04 Predictive Artificial Intelligence

Example: Predictive model of tissue composition and other production factors based on the growth curves of the feedlot and other logistical factors.

Here we begin to talk about true Artificial Intelligence.

Development of complex mathematical models through Machine Learning and Deep Learning to be able to explain the past and predict the future. These models allow for a comprehensive view of the value chain unprecedented (see where everyone else is blind), and make strategic decisions with measurable return on investment (risk-free anticipation).

It is not possible to reach this point without having completed the previous steps.

05 Prescriptive Artificial Intelligence

Example 1: IC potential model of a farm for defining sales representative incentives (simplified: triangle origin, farm, sales representative).

Example 2: Transformation of the pork value chain from push to pull.

For the simplest situations, from a predictive model an expert human can extract immediate value by applying their business knowledge. In other situations, combining Machine Learning with other branches of mathematics, one can make algorithms automatically prescribe the actions to be taken or even carry them out.

This allows us to make strategic decisions with measurable return on investment (risk-free and fast anticipation).