Agriculture departments need timely visibility into events that can affect farmers, crops, markets, and field operations. They also stand to gain from what is happening beyond their own state: how other regions are responding to similar problems, and which practices and field experiments are showing results that could be adapted locally. This information is spread across news sources in many languages, which makes it hard to follow consistently.
The Challenge
Our AI Solution
IANM is an AI-powered solution that helps state agriculture departments identify and track agriculture-related news and events in near-real time.
The AI solution scans news articles across regional languages and classifies each one as positive or negative, so departments can quickly see what needs attention.
How it Works
01
News is Collected Automatically
IANM draws on Google Alerts, an archive of the public web, and custom-built crawlers for approved regional and national news sources.
News is Collected Automatically
IANM draws on Google Alerts, an archive of the public web, and custom-built crawlers for approved regional and national news sources.
02
AI Models Analyze and Classify Content
The solution scans agriculture news across 12 languages and filters it through 19 categories and 496 subcategories.
AI Models Analyze and Classify Content
The solution scans agriculture news across 12 languages and filters it through 19 categories and 496 subcategories.
03
Events are Structured For Action
For every event, IANM extracts the headline, date, source, location, crop, severity, category, and sentiment (positive/negative).
Events are Structured For Action
For every event, IANM extracts the headline, date, source, location, crop, severity, category, and sentiment (positive/negative).
04
Events are Refreshed Continuously
The system refreshes every 2 hours, enabling near real-time visibility into emerging agriculture-related events.
Events are Refreshed Continuously
The system refreshes every 2 hours, enabling near real-time visibility into emerging agriculture-related events.
05
Alerts are Reviewed Before Action
Every flagged event is reviewed by a person before it reaches a decision-maker, helping validate the information first.
Alerts are Reviewed Before Action
Every flagged event is reviewed by a person before it reaches a decision-maker, helping validate the information first.
06
Events are Delivered into Existing Workflows
AI-shortlisted events are delivered through a portal or API that plugs into a state’s existing government systems for assignment, investigation, and closure.
Events are Delivered into Existing Workflows
AI-shortlisted events are delivered through a portal or API that plugs into a state’s existing government systems for assignment, investigation, and closure.
Where It's Being Tested
IANM is being tested in Andhra Pradesh and Rajasthan through partnerships with agencies like Kisan Sanchar.
28
States
8
Union Territories
Impact
IANM enables faster visibility into emerging agriculture-related events, a multilingual view of agriculture news across regions and sources, structured information for review, prioritization, and field-level follow-up, and integration with existing state systems rather than replacing established workflows. Once IANM is live with state partners, this section should be updated with adoption metrics—states/departments onboarded, events processed, and field actions closed.
Our Other Solutions
Partners
Looking Ahead
IANM opens possibilities for deeper AI-enabled agriculture intelligence systems by enabling structured monitoring of crop-damaging incidents and emerging risks through AI-powered media scanning. Future integration possibilities include publishing agriculture alerts directly to farmers, augmenting agricultural knowledge management systems, and building smarter alerting workflows for faster response and coordination.