Data AnalysisVerified

Reviewed and published by trentmaziarz, July 20, 2026. Discovered and drafted by our automated research pipeline.

Indigo Ag uses a machine learning platform called Atlas — built on technology from TellusLabs, which Indigo acquired in 2018 — to analyze satellite imagery, weather data, and historical records in order to forecast crop yields and monitor crop health daily across global farmlands. The system produces field-level predictions and soil maps that agronomists and farmers use to make planting and marketing decisions.

Details

Atlas combines remote sensing, ground equipment data, and weather inputs, applying machine learning models trained on over a decade of historical satellite imagery to predict end-of-season yields and identify differences in crop performance across regions. According to a Geospatial World case study, in 2017 Indigo's models predicted final US corn yield within 1% of the actual figure, five months before the USDA's end-of-season report. The platform also delineates field boundaries from imagery and characterizes local soil conditions. The underlying product originated at TellusLabs, which was acquired by Indigo in December 2018 and integrated as its Geospatial Innovation unit.

Products affected

Indigo AtlasIndigo Carbon

Sources & Evidence

News Article

Using Satellite Imagery and Machine Learning to Address Climate Challenges in Agriculture

Geospatial World·May 2022

https://geospatialworld.net/prime/case-study/agritech/using-satellite-imagery-and-machine-learning-to-address-climate-challenges-in-agriculture/

News Article

Indigo Ag Pursues Innovation and Discovery in the Soil, from Orbit

Esri / WhereNext·Jan 2020

https://www.esri.com/about/newsroom/publications/wherenext/indigo-ag-pursues-innovation-in-the-dirt-and-from-outer-space

Company Disclosure

Indigo Ag, Inc. Acquires TellusLabs, a Leader in Satellite Technology and Artificial Intelligence

Flagship Pioneering·Dec 2018

https://www.flagshippioneering.com/news/press-release/indigo-ag-inc-acquires-telluslabs-a-leader-in-satellite-technology-and-artificial-intelligence-to-enhance-indigos-data-driven-agronomic-solutions

Cite this record

Trace Foundation. (2026). Indigo Ag: Indigo Ag uses a machine learning platform called Atlas — built on technology from TellusLabs, which Indigo acquired in 2018 — to analyze satellite imagery, weather data, and historical records in order to forecast crop yields and monitor crop health daily across global farmlands. The system produces field-level predictions and soil maps that agronomists and farmers use to make planting and marketing decisions (data as of 2026-07-20) [Data set record]. AI Trace. https://www.aitrace.org/r/practice/9eb92175-0bd2-4f2f-b532-fc7a60fd0a94. Accessed September 4, 2026.

Stable link: https://www.aitrace.org/r/practice/9eb92175-0bd2-4f2f-b532-fc7a60fd0a94
Data as of: July 20, 2026
Last verified: Not recorded

How to cite AI Trace

Other practices by Indigo Ag

Data AnalysisIndigo Ag uses machine learning and data analytics to identify and nominate beneficial microbial strains from its library of 36,000+ microbes as candidates for biological seed treatment product development. This AI-assisted screening is part of the company's internal research and development process for its biotrinsic product line.Customer SvcIndigo Ag deployed an AI chatbot integrated into a redesigned buyer data portal for corporate buyers of its soil carbon credits, announced alongside the company's fifth carbon credit issuance in February 2026. The chatbot is intended to help corporate buyers conduct due diligence on carbon credit purchases with greater ease and transparency.OtherIndigo Ag announced in June 2026 that its Source business — a digital platform connecting farmers, enterprises, and governments through sustainability program management and AI-powered agricultural analytics — has been combined with CIBO Technologies to form a new company called Terion, announced by parent company Flagship Pioneering. Indigo Ag's Source practice, which was active before the formation of Terion, used AI capabilities to measure, verify, and manage agricultural sustainability programs at scale.

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