AI Usage at a Glance
Timeline
Dec 13, 2018
RecommendationPractice documented: Indigo Ag uses satellite data and machine learning to generate personalized, field-level agronomic recommendations for farmers, including which seed treatments best match a given field's soil conditions, yield potential, and environmental stressors. These recommendations are delivered through agronomists and Indigo's digital platform.
Practice DocumentedView practice →Dec 13, 2018
Data AnalysisPractice documented: 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.
Practice DocumentedView practice →Feb 14, 2019
RecommendationNew evidence: Machine Learning in Agricultural Planting, Growing, and Harvesting Contexts
Evidence AddedView practice →Jan 1, 2020
RecommendationNew evidence: Indigo Ag Pursues Innovation and Discovery in the Soil, from Orbit
Evidence AddedView practice →Jan 1, 2020
Data AnalysisNew evidence: Indigo Ag Pursues Innovation and Discovery in the Soil, from Orbit
Evidence AddedView practice →Feb 3, 2021
Data AnalysisPractice documented: 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.
Practice DocumentedView practice →May 17, 2022
Data AnalysisNew evidence: Using Satellite Imagery and Machine Learning to Address Climate Challenges in Agriculture
Evidence AddedView practice →Jan 1, 2023
Data AnalysisPractice documented: Indigo 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.
Practice DocumentedView practice →Apr 29, 2024
Data AnalysisNew evidence: Navigate New Low-Carbon Biofuel Opportunities with Indigo's Sustainability Platform
Evidence AddedView practice →Feb 25, 2026
Customer SvcPractice documented: Indigo 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.
Practice DocumentedView practice →Jun 18, 2026
OtherPractice documented: Indigo 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.
Practice DocumentedView practice →Recent activity
Indigo 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.
Indigo's official biologicals science page states that the company's biological science practice leverages microbiology, machine learning, and digital innovation. A separate company blog post describes that Indigo uses data from its microbial library to predict or nominate which strains might be the best candidates for testing in its R&D pipeline to build new biological products. A third-party case study further notes that the company invests heavily in understanding plant-microbe interactions, using machine learning and data analytics to identify beneficial microbes that enhance crop performance under various environmental conditions.
Indigo 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.
Indigo's official press release from February 25, 2026 states that a redesigned buyer data portal with an integrated AI chatbot was rolled out as part of platform upgrades to its digital monitoring, reporting, and verification (dMRV) system. The same release confirms that new remote-sensing algorithms were also deployed simultaneously to improve field and land management validation. No further technical detail about the chatbot's underlying model or vendor is disclosed in available sources.
Indigo 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.
According to a June 18, 2026 press release from Flagship Pioneering (and mirrored on Indigo Ag's own news page), Source by Indigo and CIBO Technologies merged to form Terion, a new entity whose AI-enabled platform measures, configures, deploys, and manages agricultural programs across multiple stakeholders and geographies. The combined entity brings together capabilities including scientific modeling, MRV (measurement, reporting, and verification), grower engagement, enterprise program deployment, and AI-enabled agricultural analytics. Indigo Ag's homepage as of June 2026 confirms that Indigo Ag itself remains focused on carbon programs and biological solutions, while Terion advances the next generation of digital agriculture platforms — indicating the Source AI platform practice has transitioned to the Terion entity.
All practices by category
Indigo 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.
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.
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.
Cite this record
Trace Foundation. (2026). Indigo Ag: documented AI practices (data as of 2026-07-20) [Data set record]. AI Trace. https://www.aitrace.org/r/company/6f7a99ef-85dc-4849-bb75-e576bddc78f6. Accessed October 5, 2026.
- Stable link
- https://www.aitrace.org/r/company/6f7a99ef-85dc-4849-bb75-e576bddc78f6
- Data as of
- July 20, 2026
- Last verified
- Not recorded
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