This startup manufactures biofertilizers by utilizing advanced technology to identify optimal plant-bacteria combinations tailored to specific soil types and high-protein crops. Their products enhance crop yields while reducing reliance on chemical fertilizers, promoting sustainable agricultural practices.
Funding
$540K 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
Conventional "one-size-fits-all" biostimulants often fail to deliver consistent results due to variations in soil composition, crop type, and plant-bacteria interactions. This inconsistency leads to unpredictable crop yields and continued reliance on chemical fertilizers.
Solution
SymbioMatch utilizes machine learning to analyze crop and soil data, identifying optimal plant-bacteria combinations for tailored biostimulant formulations. These biostimulants are applied directly to seeds, integrating seamlessly with existing sowing equipment. By tracking beneficial soil bacteria, assessing plant growth, and standardizing complex data, SymbioMatch develops precisely targeted, high-performance biofertilizers optimized for specific crops and soil conditions. This approach enhances farming efficiency and promotes sustainable agricultural practices by reducing the need for chemical inputs.
Target Audience
SymbioMatch targets farmers growing high-protein crops, particularly legumes, seeking to improve yields and reduce their dependence on chemical fertilizers.
Features
- Machine-learning platform analyzes crop and soil data to determine optimal bacteria-crop combinations.
- Biostimulant formulations tailored to specific soil types and high-protein crops.
- Seed coating technology allows for direct application with existing sowing equipment.
- Molecular tools track beneficial soil bacteria.
- Plant growth assessments evaluate bacterial effectiveness.
- Deep learning techniques interpret complex data sets.