GG Krishi
WhatsApp-first verification system that validates field images with AI, routes edge cases to review, and supports automated farmer reward flows.
What the product covers.
GG Krishi turns a WhatsApp chat into an auditable MRV workflow. Farmers submit images from the field, AI checks image quality and evidence, duplicate/suspicious cases move into review, and the admin portal tracks users, sessions, CRM follow-up, support tickets, analytics, and reward/payment status.
The decisions inside the build.
A concise account of the operating problem, the resulting system shape, and the technical decision that kept the work coherent.
Problem
Field verification had to work without forcing farmers into a separate application while still collecting identity, location, media, and an auditable review trail.
System shape
Persisted WhatsApp sessions connect QR identity, farmer onboarding, GPS, photo evidence, duplicate checks, vision signals, operator review, and operations reporting in one resumable journey.
Decision record
Interruptions are treated as normal. Sessions can resume safely, duplicate evidence is flagged, and AI produces review signals without becoming the final decision-maker.
What the contribution actually covered.
Presented as an MVP. The page does not claim production payouts, issued carbon credits, blockchain verification, or automated rejection.
- 01
English and Hindi registration, onboarding, evidence capture, support, and status journeys.
- 02
Responsive operations workspace for submissions, audit records, sessions, and support cases.
- 03
Persisted workflow state with linked evidence records and operator-led review.
The working parts, without the theatre.
- 01WhatsApp API
- 02AI Vision
- 03Admin CRM
This was a private engagement, so the public note is intentionally limited to the verified project scope.
Presented as an MVP. The page does not claim production payouts, issued carbon credits, blockchain verification, or automated rejection.
No public destination published