CIVIC INTELLIGENCE FOR CLEANER CITIES

Snap it.
Map it.
Gone.

Sweepzy turns a 10-second photo into an AI-verified cleanup. Report litter, watch your ward's Cleanliness Index climb, and get your street back.

400+ reports resolved 150 kg waste cleared 87% resolved < 3 weeks
SweepzySweepzy
01 · SNAP 02 · PIN 03 · SWEEP
◉ CAMERA AUTO GEO-TAG · ON
MIXED WASTE · 94%
LIVE MAP · WARD 68
Report #4821 · KR Market Rd
PINNED ✓ CREW NOTIFIED ✓
AI VERIFIED ✓
96% MATCH
Ward 68 Index +12 14 BAGS · 2H 10M
SNAP
PIN
SWEEP
AI VERIFIED · 96% MATCH
CLEANLINESS INDEX +12
HOTSPOT PREDICTED · HSR 4TH
RESOLVED Indiranagar 2nd Stage · 12 bags · verified 96%
NEW REPORT Church St · overflowing bin · 2 min ago
DRIVE SCHEDULED HSR 4th Block · Sat 7 AM · 24 going
INDEX UP Jayanagar +4 pts this week
HOTSPOT FLAGGED KR Market · 89% recurrence risk
SPONSOR JOINED Vivida Dynamics adopts Ward 68
RESOLVED Indiranagar 2nd Stage · 12 bags · verified 96%
NEW REPORT Church St · overflowing bin · 2 min ago
DRIVE SCHEDULED HSR 4th Block · Sat 7 AM · 24 going
INDEX UP Jayanagar +4 pts this week
HOTSPOT FLAGGED KR Market · 89% recurrence risk
SPONSOR JOINED Vivida Dynamics adopts Ward 68
HOW IT WORKS

Ten seconds to a
tracked cleanup.

NO FORMS · NO LOGIN WALL · NO FRICTION
01

Snap

See it? Shoot it. One photo - the geo-tag, timestamp and waste category are handled automatically.

02

Pin

Your report lands on the live city map - visible to neighbors, cleanup crews and sponsors in real time.

03

Sweep

A crew claims it. Before/after proof gets AI-verified, the pin turns green, and the ward's Index climbs.

THE AI LAYER

A brain behind
every broom.

Reporting is the easy part. Sweepzy's models handle the hard part - trust, priorities, and proof.

01 · VISION MODEL

AI Cleanup Verification

No proof, no badge. A vision model compares before/after shots and signs off every cleanup - trust, automated.

BEFORE
VERIFIED ✓ AFTER
MATCH CONFIDENCE96%
02 · LIVE SCORING

Cleanliness Index & Heatmap

Every ward scored 0–100, recalculated with every report and resolution. One number a neighborhood can rally around.

Indiranagar
84 +6
Koramangala
78 +4
HSR Layout
66 +9
Whitefield
54 -3
NEEDS LOVE → CLEAN
03 · FORECASTING

Predictive Waste Hotspots

Litter has habits. The model learns where trash returns and flags it before the pile-up - so crews arrive first.

KR MARKET · 89% RISK · TUE
NEXT 7 DAYS3 HOTSPOTS FLAGGED
04 · FOR SPONSORS

CSR & Impact Dashboard

Companies and NGOs sponsor wards, fund drives, and export audit-ready impact reports. Good PR - with receipts.

A
Vivida Dynamics
SPONSORING WARD 68 · Q2
ACTIVE
MARAPRMAYJUN
₹2.4L FUNDED · 8 DRIVES · 3.1 t CLEARED EXPORT REPORT ⤓
LIVE MAP

One city.
Every report.

BENGALURU · LIVE
OPEN DRIVE PREDICTED
CITY CLEANLINESS INDEX
71/ 100▲ +4 this month
TODAY, SO FAR
New reports38
Cleanups verified26
Drives this weekend6
Hotspots flagged3
Open the full map →
IMPACT SO FAR
400+
REPORTS RESOLVED
10
CLEANUP DRIVES
150 Kg
WASTE CLEARED
500+
Community Members
RECEIPTS

Pics or it
didn't happen.

EVERY RESOLVED REPORT SHIPS WITH AI-VERIFIED BEFORE/AFTER PROOF. DRAG THE HANDLE TO COMPARE.
KR Market after cleanup AFTER · VERIFIED ✓
KR Market before cleanup BEFORE
◂▸
DRIVE #198 · KR MARKET 31 BAGS · 40 VOLUNTEERS · AI MATCH 98%
Church St after cleanup AFTER ✓
Church St before cleanup BEFORE
◂▸
REPORT #4821 · CHURCH ST 6 BAGS · SAME DAY · 93%
HSR Layout after cleanup AFTER ✓
HSR Layout before cleanup BEFORE
◂▸
DRIVE #212 · HSR LAYOUT 14 BAGS · 2H 10M · 96%
WHY I BUILT THIS

When "India"
became the answer.

I was watching a GeoGuessr livestream, a game where players guess a location from random Google Street View images. Every time the street looked dirty or covered in litter, the livestream chat instantly filled with the same answer: "India."

It bothered me. Seeing my country reduced to a stereotype was disappointing. But at the same time, I couldn't honestly say they were completely wrong. Poor waste management and weak civic participation are problems we still struggle with. Instead of complaining about it, I decided to build something that could help.

That's how Sweepzy started. I'm building it end-to-end, from product and design to the backend, AI pipeline, and deployment. The goal is simple: make reporting litter take seconds, give communities a shared map of issues, use AI to verify cleanups, score ward performance, and help cities stay cleaner through better civic participation.

Next.js FastAPI PostGIS Vision models
JOIN IN

Your street is one
photo away.