Evja utilizes wireless sensors and artificial intelligence to optimize irrigation, nutrition, and crop protection by providing real-time data analysis for precision agriculture. This technology enables growers to enhance water management, predict yields, and reduce chemical usage, ultimately improving crop quality and productivity.
Funding
$5.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Growers often lack precise, real-time data on key environmental factors such as soil moisture, nutrient levels, and weather conditions, making it difficult to optimize irrigation, fertilization, and crop protection strategies. This can lead to inefficient resource use, reduced yields, and increased environmental impact.
Solution
Evja provides an advanced system for precision agriculture that combines wireless sensors and artificial intelligence to optimize crop management. The system, called OPI, harvests data from the field using innovative wireless sensors and processes it with AI to define predictive models tailored to specific grower goals. This enables growers to monitor irrigation, nutrition, and crop protection in real-time, allowing for better water management, yield prediction, and reduced chemical usage. Users can access key information anytime on PC, tablet, or smartphone to improve planning and decision-making.
Target Audience
Evja targets growers of annual crops, vineyards, and tree fruit and nut orchards, as well as agricultural consultants and researchers seeking to optimize resource management and improve crop yields.
Features
- Wireless soil sensors for real-time monitoring of soil moisture, salinity, and temperature
- AI-powered predictive models for irrigation, fertilization, and crop protection
- Yield prediction models calibrated on specific crops
- Disease predictive models customized for specific crops
- Web and mobile app for accessing key information and improving planning
- Integration with weather forecasts for proactive decision-making
- Data-driven insights for optimizing the timing of fertilizations