Indigo Ag uses proprietary remote-sensing algorithms, powered by machine learning and increasingly AI, to validate that farmers have adopted specific regenerative land-management practices across enrolled fields, enabling the company to issue verified soil carbon credits without visiting every acre in person. This system underlies Indigo Carbon, the company's soil carbon program, which had enrolled more than 8 million acres across 28 US states as of February 2026.

According to Indigo's own engineering blog, the company built a suite of models tuned on satellite remote-sensing and weather data to automatically detect regenerative agricultural practices (such as no-till farming and cover crops) on enrolled fields and monitor crop health during the growing season. A separate company blog post from 2024 confirms that, through proprietary technology employing advanced image processing, machine learning, and AI, Indigo built a comprehensive field-scale atlas of US agriculture, delineating field boundaries from imagery and generating seasonal models to identify management practices and quantify emissions. Indigo's carbon resources page states that proprietary remote-sensing algorithms validate management data at scale as part of its carbon accounting workflow.