Global AI Impact Commons
Advanced Roaster Data Processing and Analysis System
Sri Lanka
Agriculture
Implementing Organisation
Rootcode
Sri Lanka, Western Province, Colombo
Implementing Point of Contact
Alagan Mahalingam
Founder & CEO
Contributor of the Impact Story
Rootcode
Year of implementation
2023
Problem statement
Global food security and agricultural planning efforts are constrained by limited access to timely, accurate insights on crop conditions, land use, and agricultural productivity. Existing monitoring approaches often fail to effectively integrate satellite imagery and geographic data, making it difficult to support strategic decision-making and ensure compliance in agricultural systems. Rootcode fills this gap by integrating satellite imagery and geographic data to support global food security and agricultural monitoring efforts.
Impact story details
Rootcode is a global technology company founded in Sri Lanka, specializing in AI platforms and software solutions for European governments and Fortune 500 companies. With 115+ employees across Sri Lanka, Estonia, and the US, Rootcode has won competitive government contracts in Estonia, Portugal, and Czech Republic, often against major consulting firms like Accenture and IBM. The company holds ISO 9001 and ISO 27001 certifications and has been recognized with multiple awards including the Asia Pacific ICT Awards 2025 (#1 in Asia Pacific). Rootcode also operates the Rootcode Foundation, providing technology education to over 1,000 underprivileged students in Sri Lanka.
AI Technology Used
Key Outcomes
Efficiency
Productivity, Accuracy
Quality Improvement Access
Reach, Knowledge
Skills Impact
Impact Metrics
Time reduction in processing and analyzing raster data for agricultural decision-making
Post-Implementation
Near real-time analysis capability
Implementation Context
Southeast Asia, Afghanistan (in partnership with Geo-Informatics Center, Thailand)
FAO officials and policy makers working on food security and agricultural development across Southeast Asia and Afghanistan
Key Partnerships
International Organization (UN Food and Agriculture Organization), Academia/Research (Geo-Informatics Center / GIC, a leading remote sensing and GIS organization in Southeast Asia since 1995
Replicability & Adaptation
Similar raster data processing systems can be adapted for different geographic regions by incorporating region-specific satellite imagery and agricultural data. Local calibration of algorithms may be required based on crop types, climate conditions, and available data sources. Integration with existing national agricultural information systems would enhance adoption.
Supporting Materials
* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.