Summaryagricultural lending is the backbone of rural economies, yet today's methods for verifying cattle herds (the collateral behind billions of dollars in loans) are outdated, costly, and prone to…

The Department of Agriculture National Institute of Food and Agriculture awarded Flyover Ventures, Inc. (operating as Boveye) $131,500 under the Small Business Innovation Research (SBIR) Program on September 15, 2025.

The recipient is developing a satellite imagery and artificial intelligence system to remotely identify and count cattle on pastures and feedyards while simultaneously measuring pasture health. The technology generates georeferenced, time-stamped, and tamper-proof digital reports designed to replace costly in-person livestock inspections for agricultural lending collateral verification. The system addresses current vulnerabilities in cattle herd verification used to secure billions of dollars in agricultural loans, targeting cost reduction for lenders and producers while improving loan accessibility for small and beginning ranchers.

Performance occurs in North Bend, Nebraska. The period of performance runs through July 31, 2026. As a Phase I SBIR award, the project focuses on demonstrating technical feasibility of the proposed innovation and bringing it closer to commercialization, with the expectation that successful Phase I completion may support Phase II funding for continued research and development.

Summaryagricultural lending is the backbone of rural economies, yet today's methods for verifying cattle herds (the collateral behind billions of dollars in loans) are outdated, costly, and prone to error or fraud. Lenders often rely on in-person inspections, which require long-distance travel, 'eyeballing' headcounts, and come with biosecurity risks from visiting multiple ranches. This creates high costs for banks and producers alike, while leaving financial institutions vulnerable to fraud estimated in the billions annually. The consequences extend beyond lenders and producers: weakened rural banks affect community stability, limit access to affordable credit, and reduce the resilience of america's food and agricultural systems. Finding a more reliable, scalable, and cost-effective way to verify cattle inventories is therefore both an economic and community imperative. This project will explore how high-resolution satellite imagery, combined with advanced artificial intelligence (AI) models, can be used to remotely identify cattle on pastures and feedyards while also measuring pasture health - providing a dual-use benefit from a single image. By combining cattle counts with pasture condition indicators, the project will generate digital reports that are georeferenced, time-stamped, and tamper-proof, designed to meet the strict requirements of regulators and lenders. These methods replace costly on-the-ground inspections with a tool that can be scaled to thousands of operations in a way that is safer, faster, and more affordable.if successful, this research will deliver significant benefits not only to agricultural lenders and producers, but also to rural communities and the broader public. Banks will reduce losses and compliance costs, allowing them to extend more credit at lower risk. Producers will gain access to more affordable financing, particularly small and beginning ranchers who are most affected by high inspection costs. Regulators will have stronger safeguards against fraud, improving the stability of agricultural finance. In short, this project combines cutting-edge technology with a practical financial application that strengthens rural economies, protects taxpayers, and supports the long-term health of america's food system.