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Agrivoltaics developer brings Stanford modeling platform in-house to build better solar + crops

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29/12/2025
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Agrivoltaics developer brings Stanford modeling platform in-house to build better solar + crops
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Agrivoltaic project developer Okovate Sustainable Energy has acquired the assets of Fundusol, a modeling platform born out of Stanford University and Carnegie Mellon. This acquisition, supported by Okovate’s backing from The Schmidt Family Foundation, brings data-driven precision to the co-location of solar energy and agriculture.

An agrivoltaics installation. Credit: Green Development

Okovate is now integrating Fundusol’s proprietary modeling engine — a sophisticated technology stack designed to simulate the complex interactions between solar array architecture and crop phenology — directly into its development pipeline. The acquisition allows Okovate to move beyond traditional development to become a technical data partner for the agricultural community.

“By acquiring the Fundusol platform, Okovate is delivering on its mission to make agrivoltaics a reliable, data-driven reality for the American farmer,” said Miles Braxton, CEO of Okovate. “We are building predictive AI tools on top of this genomic modeling engine to translate complex solar engineering into actionable insights for rural farmers. This ensures that we aren’t just building energy projects; we are providing the data-driven clarity needed to strengthen the economic fabric of our farming communities.”

The Science of Symbiosis The integrated platform utilizes the SIMulated PLant Ecosystem (SIMPLE) crop biomass model to project outcomes for over 60 different crop types. By merging this framework with proprietary irradiance and thermal dynamics models, Okovate provides:

  • Genomic Optimization: Utilizing a custom, in-house genetic algorithm to determine the ideal solar array configurations — such as panel spacing, height and tilt — specifically tailored to the light saturation needs of individual crops.
  • Precision Phenology Insights: High-fidelity modeling that projects how specific crops will respond to the microclimates created by solar infrastructure.
  • Advanced Data Visualization: Leveraging 3D system representations and digital twins to allow farmers and landowners to visualize optimized farm layouts before construction begins.

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