Avalo utilizes a natural, non-GMO, AI-powered platform to accelerate plant evolution for agriculture. This process rapidly develops crop varieties with enhanced resilience, reduced input requirements, and improved yield potential. The technology delivers tailored genetic adaptations to address changing climates and market demands more efficiently than traditional breeding.
Funding
$15.6M 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 crop breeding methods struggle to keep pace with rapidly changing climates and the increasing demand for sustainable agricultural practices. Traditional approaches often require extensive time, resources, and genetic modification, limiting the ability to quickly develop resilient and high-yielding crop varieties. This can lead to food insecurity and environmental degradation due to reliance on resource-intensive farming methods.
Solution
Avalo employs a Rapid Evolution platform, leveraging non-GMO techniques and artificial intelligence, to accelerate the development of climate-resilient and sustainable crop varieties. This platform analyzes broader gene pools, wild varieties, and natural pollination data to identify desirable traits and predict breeding outcomes. By integrating scalable predictive modeling and whole-genome analysis, Avalo can efficiently select for complex, multi-trait characteristics, such as drought tolerance, pest resistance, and enhanced nutritional content. The result is a faster, more affordable, and scalable approach to crop breeding that improves genetic diversity and reduces the need for water, fertilizers, and pesticides.
Target Audience
Avalo's primary customers include farmers seeking resilient and profitable crop varieties, manufacturers requiring sustainable ingredients, and agricultural partners aiming to improve breeding efficiency.
Features
- Rapid Evolution platform using non-GMO, nature-based processes
- AI-powered predictive modeling for faster trait selection
- Whole-genome analysis to identify complex genetic characteristics
- Development of crops tailored for specific geographic regions and climates
- Breeding for input reduction, including less water, fertilizer, and pesticides
- Enhanced climate resilience for crops in harsher environmental conditions
- Improved crop efficiency, with higher yields on less land
- Enhanced nutritional content and flavor profiles