Machine Learning at re.green: transforming the land acquisition and analysis process
The Machine Learning challenge arose due to the need to reduce the divergence found by re.green between manual and automatic analyses of the captured lands.
The Machine Learning challenge arose due to the need to reduce the divergence found by re.green between manual and automatic analyses of the captured lands.
Article reveals in detail the structuring process of the data architecture that enables the effective land monitoring by re.green.
The article highlights the importance of viewing data as digital assets capable of generating new revenue, reducing costs, optimizing internal processes, and providing solutions to third parties.
Learn how re.green, with support from EloGroup, made its operations more efficient, scalable, and accurate through a full-stack technology solution.
Trends include the use of data, artificial intelligence, and technology to optimize operations and deliver a better user experience.
In its 7th edition, the 100 Startups to Watch (100 STW) award highlights the most promising companies in the fields of entrepreneurship, technology, and innovation across the main economic sectors in Brazil in 2024.
An EloGroup case of Shared Cost Center in a global agro-mining company that translated into significant results and improved efficiency
A continuous cycle that helps maintain competitiveness and involves changes in processes, people and technology. We have listed 10 actions and points of view for a transformation with purpose and solid foundations.
The automation method developed by EloGroup allows an organization to go from a desire for digital transformation to a fully functional, approved system in production in 30 days.
