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Home - News - Agrivoltaics developer brings Stanford modeling platform in-house to build better solar and crop plants
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Agrivoltaics developer brings Stanford modeling platform in-house to build better solar and crop plants

solarenergyBy solarenergyDecember 30, 2025No Comments2 Mins Read
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Agrivoltaic project developer Okovate Sustainable Energy has acquired the assets of Fundusola modeling platform born from Stanford University and Carnegie Mellon. This acquisition, supported by support from Okovate of The Schmidt Family Foundation, brings data-driven precision to the co-location of solar and agriculture.

An agrivoltaic installation. Credit: Green Development

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

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

The Science of Symbiosis The integrated platform uses the SIMulated PLAnt Ecosystem (SIMPLE) crop biomass model to project results for more than 60 different crop species. By combining this framework with proprietary irradiance and thermal dynamics models, Okovate offers:

  • Genomic Optimization: Using a custom, in-house genetic algorithm to determine ideal solar panel 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: Using 3D system representations and digital twins, farmers and landowners can visualize optimized farm layouts before construction begins.
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