Bringing technology closer to users

We develop platforms driven by neural network training and decision trees. We use Machine Learning as well as Deep Learning to optimize processes. Our goal is to simplify cutting-edge technologies, giving users intuitive ways to carry out complex tasks. We aspire to democratize access and use of these advanced tools, improving usability in different fields.

We implement blockchain technology to safeguard data integrity and transparency while transactions are carried out on our web platforms. We guarantee data immutability by registering each transaction in interconnected encrypted blocks. This encryption guarantees that any attempt at alteration will be recorded and visible in the blockchain, providing an extra layer of security and verification throughout the entire process.

We analyze an extensive amount of data, from both public and private databases, to carry out statistical analyses and foresee patterns and trends. Our web platforms are focused on implementing predictive models for data analysis, including models derived from images. Our main goal is to facilitate decision making both on the platform and for users and their companies.

We integrate into our processes the data provided by IoT sensors installed by our users. This data is presented on our web platform both visually and numerically, broadening the understanding of the data and its implications. This integration allows us to develop tools with high added value for our clients and users, optimizing productive processes and the analysis of the collected data.

Creating 3D models of land and crops makes it possible to calculate tree cover as well as the measurements, areas, and volumes of crops and cultivated land. This makes it possible to plan more precise agricultural strategies, which in turn leads to a more effective use of resources and increased agricultural productivity.

We optimize processes related to the construction and maintenance of structures, infrastructures, and components thereof through the use of 3D models generated by any camera or imported from a laser scanner. This allows for an in-depth analysis and detailed study of these structures, and makes it possible to compare them to the IFC models generated during the planning stage. In this way, we are able to determine the degree to which the IFC models and the 3D representations are alike, significantly optimizing processes.

We use Artificial Intelligence to automate and optimize traffic signal inspections, streamlining the inventory of vertical and horizontal signs, along with road surface damages and imperfections. We also assess signs’ level of retroreflectivity, helping to improve road safety.