Research and access for Indian property
The signal for where property is heading already exists, scattered across records that nobody has joined. Joined, it shows an area turning two to four years before any price index registers it. We are building the engine that reads it, and the schemes that let ordinary investors own a share of what it finds.
Wakad is not one place. The lanes beside the IT park and the lanes behind it have different water, different roads, different rent, and the same postcode. The engine works at this resolution, and redraws the boundary for every search.
Wakad, Pune · 7.1 km²
Walk through Area SearchDifferent people, different pricing, different timelines. Only one of them is never for sale. Open any line to read the thinking behind it.
Taking leave to go and look. Brokers who show only what they are selling. Weeks of searching that still end in the wrong area, and finding out eighteen months later what living there actually costs.
EPFO records 150,000 formal job switches every month, 1.8 million a year, counting only those who transferred their accumulations. Most end in no move at all. The answer is bought either way.
Two inputs. Anything someone would weigh about a place: commute, schools, water, roads, safety, the tier of the locality, each ranked one to five. And what they can spend on each.
Back come ranked pockets that fit the budget, each with what living there would cost every month, and the specific schools, routes and homes behind that number.
It earns from day one, needs little capital, and runs on the same pipelines the engine needs. Every search is demand behaviour no filing contains.
Existing platforms help you search for a property to buy. None of them tell you whether it is a good investment. That research layer simply does not exist in India. Every SM REIT platform monetises only its own schemes.
Subscriptions fund the build. And every search, shortlist and comparison is demand data no rival has, and it feeds the engine.
Buyers and investors by subscription, tiered for individuals and professionals.
A developer registers land. A road tender is issued. An employer signs a large lease three kilometres away. Project filings in that pincode jump from two to nine. Utility connections rise.
Each record is unremarkable alone, and each sits with a different authority in a different format. Nobody has a reason to join them. Joined, they say one thing: this area is about to move, two to four years before any price index registers it.
Two sources, always. Public filings give the history but are lagged and thin. Our own network gathers what no filing contains, directly and continuously. Above both sit rates, credit, jobs, sector health, policy and global trade.
It looks for links across hundreds of parameters that no one would connect by hand. Past cycles teach it which shocks moved which markets, how far and after how long. Then it runs today forward.
The engine surfaces candidates and shows every record behind each flag. Our team investigates and chooses. The machine flags, a human decides, the machine learns.
Every scheme we run feeds the model what actually happened. The model gets better, so the flags get better, so we buy better buildings. The lead widens every year instead of eroding.
Pooled investing already works this way everywhere else. A vehicle holds many assets, you hold units of the vehicle, and you get exposure to all of them without picking any yourself.
A Cosmorra scheme would hold stakes in several buildings across one city, and you would hold units of the scheme. Diversified exposure, without choosing a building yourself.
Every SM REIT scheme listed in India is one building with one tenant. If that tenant exits or one micro-market softens, investors absorb the whole downside with no portfolio buffer.
The engine chooses; the vehicle is downstream and can change. SM REIT schemes today, tokenised baskets if that route is legalised. New rails make the model cheaper to run, not obsolete.
It needs regulatory steps first: Investment Manager registration, net worth thresholds, a trustee. Today the minimum ticket is set at ten lakh by regulation, and that barrier has fallen three times before in this asset class.
Everything that has already happened, we sell. What is about to happen stays inside.
Facts and track records. No recommendations, no tips.
Never sold, never licensed. It selects what goes into our own schemes, and it is proven by what those schemes return, published every quarter.
A locality average is useless when the two halves of it have nothing in common. We group streets by where your factors actually stay consistent.
No area wins on everything. You rank each factor from one to five, and the model shows you what it traded away rather than hiding the compromise.
Rent is the number everyone quotes and the smallest part of the answer. School fees, commute and daily costs decide whether a place is affordable.
No filing records whether the water runs all day, how wide the road is, or what the street feels like after dark. That comes from a network we are building.
Cosmorra is early. What you see here is the design, not the product. The interface and the decision structure are real, the data and the model are being built. Nothing on this site produces a figure we do not yet have.