Source: Mint
Context:
Farmers in Maharashtra and dairy producers in Gujarat are increasingly using AI-based digital advisory tools to replace or supplement traditional knowledge networks (“village universities”) and limited access to agricultural experts.
Two major examples:
- MahaVISTAAR — crop advisory platform (Maharashtra)
- Amul’s “Sarlaben” AI assistant — dairy advisory (Gujarat)
Structural Problem AI Is Trying to Solve
Decline of Traditional Knowledge Networks
Earlier:
- Joint families and community networks shared farming knowledge.
- Experience-based local learning.
Now:
- Nuclear families
- Time constraints
- Limited extension outreach
- Need for fast, field-level decisions
➡ Farmers rely on quickest advice source.
Model 1 — MahaVISTAAR (Crop Advisory AI)
A state-backed digital platform integrating:
- University research advisories
- ICAR and Krishi Vigyan Kendra knowledge
- Weather alerts
- Pest management
- Market prices
- Scheme information
- Storage and equipment directories
Key Innovation
Source-verified knowledge pipeline
- Information not scraped from the internet.
- Directly drawn from research institutions.
➡ Emphasis on credibility and scientific authority.
Benefits Observed
- Correct dosage advice reduces input cost.
- Faster pest alerts (within 24 hours).
- Centralised decision-support tool.
- Reduced dependence on input dealers’ commercial advice.
Model 2 — Amul’s “Sarlaben” AI (Dairy Advisory)
AI-powered voice assistant for livestock management.
Functions:
- Disease guidance
- Feeding advice
- Hygiene practices
- Treatment suggestions
- Works through phone calls (even for feature phones)
Problem It Addresses
- Veterinary access delays (2–4 hours).
- Small farmers managing few animals.
- High cost of repeated vet visits.
➡ Provides immediate first-level guidance
