Advanced Analytics

Cutting-edge mathematical analyses that transform raw data into useful tools to support business strategies.

LoraWine implements Machine Learning algorithms, capable of learning from data and autonomously improving their performance over time. These models analyze the large volume of collected information to identify hidden patterns and relationships, offering increasingly accurate predictions to support business management and strategic planning.

The system is not limited to statistics: the AI Server automatically generates alerts beyond predefined thresholds, identifying anomalous patterns that could escape traditional evaluation. This predictive analysis capability allows anticipating crop needs and simulating plant development based on different climatic scenarios, providing the winemaker with a cutting-edge tool to navigate the uncertainty of climate change.

LoraWine's analyses provide immediate and daily support. The analytical architecture offers hyper-local weather forecasts to precisely plan activities, defines optimal intervention windows to guarantee maximum operational effectiveness, spatializes data collected across all different areas within vineyards to best understand development conditions, generates the most common agronomic indices and allows archiving personal annotations and laboratory analyses in an organized and secure space.

All advanced analysis mathematical models of LoraWine are developed by a team of industry experts that includes computer engineers, oenologists, agronomists and authoritative research centers.

Intervention and Effectiveness Windows

Identifying the perfect moment to intervene in the vineyard is fundamental to ensure treatment effectiveness and operator health. LoraWine leverages a dynamic calendar that cross-references predicted weather conditions, real environmental parameters with plant growth dynamics to determine the most favorable intervention windows.

LoraWine offers two useful indications regarding the optimal moment to intervene with a phytosanitary treatment and regarding the effectiveness period of the active ingredient used.

The definition of the optimal intervention moment is performed by the system considering air temperature, wind intensity, leaf wetness and soil status. Meanwhile, the definition of the effectiveness period is based on the type of product used, the amount of precipitation, air temperature and vegetative tissue growth.

LoraWine through careful monitoring and specific analyses supports the winemaker's choices with precise data, allowing timely intervention at the best moment.

Data Spatialization

Data spatialization creates detailed agricultural maps that faithfully represent the different parts of the vineyard. Using the territory's morphological characteristics and agro-meteorological parameter collection at key points, LoraWine can distribute the point parameters measured by weather stations to vineyard areas where they are absent.

This approach transforms the vineyard into a mosaic of precise, point-specific information, capable of supporting the winemaker in defining climatic events.

Analysis and Annotation Archive

With LoraWine, all agronomic and laboratory analyses, quality samplings, fermentation monitoring, and any annotations are archived in an organized and secure space divided by vineyard, wine, and vintage.

LoraWine's centralized digital archive ensures that every evaluation, oenological or agronomic, is always at hand, eliminating information dispersion and facilitating internal analysis of production results for continuous improvement.