How Grow Indigo uses Snowflake to scale data-driven agriculture

Grow Indigo, a joint venture between India’s Mahyco and US-based Indigo Ag, is leveraging technology to expand sustainable farming practices and carbon credit programs. The company works with over two million farmers across India, providing biological solutions to reduce reliance on chemical fertilizers and using artificial intelligence (AI) and satellite data to verify regenerative agriculture practices. However, scaling these efforts presented a major data challenge. With 2.5 million acres enrolled and 1,000 farmers joining its platform daily, Grow Indigo was generating vast amounts of structured and unstructured data—ranging from farm boundaries to real-time soil health metrics. Managing this data manually led to inefficiencies, security risks, and delays in decision-making. 

Before adopting Snowflake, Grow Indigo relied on traditional databases designed for transactional workloads rather than large-scale analytics. Business intelligence (BI) reports took 100 hours per month to generate, often with a week’s delay. Data silos made it difficult to access real-time insights, and enforcing security and compliance measures was cumbersome. As the company scaled, it became clear that its existing data infrastructure could not keep up. 

By migrating to Snowflake, Grow Indigo centralised all data workloads, eliminating silos and enabling real-time analytics. The shift significantly improved operational efficiency, cutting the time needed for BI report generation from 100 hours to near-instant access. AI-powered document processing reduced farmer enrollment time by 30%, bringing it down from 40–60 minutes per farmer. The elimination of replica databases lowered infrastructure costs, while AI-driven data access allowed teams to move away from static dashboards to real-time data queries. With Snowflake’s scalable architecture, the company can now manage increasing data volumes without performance bottlenecks—critical as it expands its carbon program and biological product distribution. 

Beyond improving data management, Grow Indigo is integrating AI to streamline agricultural verification processes. Currently, farm boundary validation is a manual process, but AI models are being trained to automate this step, potentially removing a major bottleneck in carbon credit certification. The company is also shifting from conventional BI dashboards to AI-powered data bots, enabling teams to query information dynamically rather than relying on pre-built reports. This move is expected to improve decision-making across sales, operations, and compliance. 

Agriculture has historically lagged in digital adoption but Grow Indigo’s use of Snowflake and AI illustrates how cloud computing can make sustainability initiatives more scalable. As agritech investment grows and carbon markets expand, the need for robust data infrastructure becomes more pressing. The challenge now is to further optimise AI capabilities and streamline verification processes, ensuring that digital transformation leads to measurable improvements in agricultural sustainability.