One kitchen.
Twelve restaurants.
Ghost kitchens are everywhere on Zomato, Swiggy, and DoorDash — a single location running six or ten "restaurants", each a different cuisine. Most aren't labelled as such. We identify virtual brand clusters from shared address, menu overlap, image reuse, and hours — so operators, investors, and brands stop analysing phantoms as individual restaurants.
Signals, not guesses
Shared address & GPS
Multiple "restaurants" with the same delivery origin are the strongest signal — when read carefully, not just string-matched.
Menu overlap
Shared dish names, pricing, and image assets across supposedly different restaurants.
Synchronised hours
Opening and closing times, temporary outages — ghost kitchens move together.
Image reuse
Perceptual image hashing across brand galleries catches reused dish and banner photography.
Promised ETA similarity
Same rider pool = almost identical ETAs to the same pin code. A telling fingerprint.
Review language signals
Reviewers frequently mention the parent operator or other virtual brands. That's a free label.
Who pays for this data
Restaurant chains & cloud kitchen operators
Know the true competitive set. A "top 20 biryani" list that treats each virtual brand as independent is misleading.
PE / VC investors
Model cloud kitchen portfolios, estimate effective volume per physical kitchen, and benchmark operators against peers.
FMCG & ingredient suppliers
Map where virtual brands concentrate to plan distribution and sampling efficiently.
Delivery platforms
Keep an outside-in view of ghost kitchen density for category health and merchant ops planning.