Messy addresses in. Routable pins out.
“Opp. gali no. 4, near shiv mandir” is a perfectly good address to a local rider. The AI Address Cleaner reads it the same way, matches the landmark, corrects the pin code and places the drop. Anything it is unsure of waits for a quick call instead of a wasted trip.
Address check · 48 orders
6 fixed · 1 to confirmopp. gali no. 4, near shiv mandir, rohini
Gali 4, opp. Shiv Mandir, Sector 16, Rohini
11008996% matchH-2/114 sec 7 behind DC chowk
H-2/114, Sector 7, behind DC Chowk, Rohini
11008593% matchpitampura TV tower ke paas, 3rd floor
Near TV Tower, Pitampura, 3rd floor
11003488% matchflat 12 mangal bazar side
Two possible matches: Budh Vihar, Sultanpuri
-Call customer to confirm
- Reads
- English, Hindi, Hinglish
- Matches
- Landmark, lane, locality
- Checks
- Pin code against locality
- Unsure
- Held for confirmation
How it runs
Four stops from start to done.
- 1
Read the address
Every order address is split into house, lane, landmark, locality, city and pin code.
- 2
Match the landmark
Temples, chowks, metro stations, schools and shops are matched to real locations.
- 3
Correct and score
Wrong or missing pin codes are fixed and each address gets a confidence score.
- 4
Confirm the doubtful
Low-confidence addresses are flagged for a call or a customer message before routing.
What is inside AI Address Cleaner.
Each part works on its own, and better with the rest of Pinsutra.
Landmark matching
Near, opposite, behind, ke paas. Directions are understood, not ignored.
Pin code repair
Pin codes that do not match the locality are corrected and noted.
Hinglish and Hindi
Addresses typed in mixed script and local spellings are read correctly.
Customer confirmation
Send a confirm-location message so customers drop a pin themselves.
Learns your area
Each confirmed delivery improves future matches for that society or lane.
Review queue
Your team sees only the addresses that need a human, not the whole list.
110089 Before and after
The same order list, ready for the road.
Address problems are the most common reason a rider circles a block. Fixing them before routing means accurate distances, honest ETAs and fewer “bhaiya, location bhejo” calls.
- “H-2/114 sec 7 behind DC chowk” placed at DC Chowk, Sector 7
- “TV tower ke paas, 3rd floor” matched to Pitampura, floor kept for the rider
- Pin 110058 on a Rohini address corrected to 110085
- Duplicate customers merged with their past delivery points
- Two possible matches held for a call, never guessed
- Floor, gate and parking notes passed to the rider app
AI suggests, people decide
- Every correction is visible and can be undone.
- Uncertain addresses are confirmed with the customer, never guessed.
- Customer addresses are used only to deliver your orders.
? AI Address Cleaner
AI Address Cleaner, answered
The things operations heads ask us in the first call, answered plainly.
Does it change the address the customer typed?
The original is always kept. Pinsutra stores a cleaned version alongside it and shows the rider both.
What happens to addresses it cannot place?
They go to a short review list. Your team can call, send a location request, or place the pin manually.
Does it work outside Delhi NCR?
Yes. Address matching covers cities and towns across India, and gets sharper in each area as deliveries are confirmed.
Can we run it without route planning?
Yes. Upload a file, get back cleaned addresses and pin codes, and use them in your own systems through the API.
Next stops on the route
13:51 Back at the hub
All pins green. Every rider home.
Free drops
500
Your first run · on us
Plan your first 500 drops free.
- Upload your Excel, see routes in minutes
- Every feature on, no card needed
- Your riders install the app in one go