REMINT

THE PROBLEM Indian cities lose the recycling battle at the doorstep. Most household waste is still handed over mixed, so wet, dry and hazardous waste end up in the same landfill. Many municipalities have tried paying citizens to sort, but those schemes are easy to fake. A photo can be reused, a pickup can be claimed without happening, and nobody can check that the waste reached a collector. Without a way to verify segregation on the ground, cities can't reward the people actually doing it.

WHAT I BUILT ReMint is a civic platform that turns waste segregation into rewards that can be checked. Credits are released only after a 5-step chain of custody is complete:

1. Report: the citizen photographs their sorted waste in the app, which records their GPS location.
2. AI check: a vision model classifies the waste as wet, dry or hazardous and scores how well it's sorted. Reused photos are rejected by fingerprinting each image.
3. Worker check: the municipal collector can only verify a pickup within 50 metres of the reported location, so it can't be done remotely.
4. Handover: the citizen shows a one-time QR code that the worker scans. The code works once and then expires, so it can't be replayed.
5. Reward: credits are recorded in a tamper-proof ledger (100 credits = ₹10) and can be redeemed for civic rewards or utility tax rebates.

WHO IT'S FOR

• Citizens: easy reporting, live pickup tracking on OpenStreetMap, a rewards wallet, streaks, badges and a ward leaderboard.
• Municipal workers: a portal with a QR scanner, a GPS proximity check and on-site sorting inspection.
• City administrators: a command centre with a ward-level map, a live feed of collections and environmental impact analytics.
• Bulk generators (housing societies, institutions) and citizens reporting illegal dumping.

WHY IT MATTERS ReMint changes "please segregate your waste" from an appeal into an incentive that can't be cheated. Every rupee a city pays out is backed by AI evidence, a GPS-verified visit and a physical handover. That gives municipalities auditable data on how much waste was sorted at source and diverted from landfill. It's built for Maharashtra, with a Marathi voice assistant to make it accessible.