Hemav's LAYERS platform utilizes artificial intelligence to develop precise crop prediction models, enabling farmers to monitor and optimize land use remotely. By providing actionable insights on crop yield and quality, the platform enhances decision-making efficiency and sustainability in agricultural practices.
Funding
Funding not disclosed
Founders
Product
Problem
Farmers often lack precise, real-time insights into crop yields and land development, hindering efficient decision-making and leading to suboptimal resource allocation. Traditional methods for crop prediction are often inaccurate, untimely, and fail to integrate diverse data sources for a comprehensive view. This results in increased waste, reduced profitability, and challenges in achieving sustainable agricultural practices.
Solution
LAYERS is an AI-powered SaaS platform designed to provide agribusinesses with accurate crop prediction and operational optimization. The platform integrates diverse data sources, including satellite imagery, meteorological data, IoT sensors, drone data, lab analyses, and public geospatial information, processing over 1.2 billion data points daily. By applying proprietary AI models, LAYERS delivers precise yield and quality forecasts, enabling informed decisions that reduce waste and maximize efficiency. The platform offers two core modules: Crop Predictor, which focuses on yield forecasting, and Crop Optimizer, which provides insights to enhance harvest outcomes.
Target Audience
The primary target audience includes agribusinesses, plantations, food producers, and financial market players involved in trading, loans, and insurance within the agricultural sector.
Features
- AI-driven crop prediction models tailored for specific crop types
- Integration of satellite imagery, meteorological data, IoT sensors, and other data sources
- Weekly crop monitoring, even on cloudy days, using SAT-TECH
- Predictive insights into yield and quality throughout the crop cycle using PREDICTIVE-TECH
- Drone data integration for counts, weed analysis, and gap analysis using DRONE-TECH
- Soil sample integration for a unified view of soil conditions using SOIL-TECH
- Customizable AI models that generate actionable data for each user