Tenant health checks before you buy a pre-leased shop or office, then watch it
TL;DR Lesseewise checks the tenant before an investor buys a pre-leased shop, showroom or office floor. It pulls company filings, tax registration status, store openings and closures and review trends into one report, then keeps watching the tenant monthly. Brokers and small property funds pay per report or per asset.
A pre-leased property is only as good as the tenant paying the rent. Yet buyers mostly check the lease and the building, not the business inside it.
Retail shows what happens when tenants leave. One large consultancy counted 64 ghost malls in 2023, malls with more than 40% vacancy, up from 57 a year earlier, with 13.3 million sq ft empty[1]. Mall leasing fell 42.1% quarter on quarter in Q3 2026 while high streets took 67.9% of retail leasing[2], and that pushes more investors toward high-street units where one tenant is the whole income. Office vacancy rose to 14.37% in the same quarter[3].
The seed pictured a broad prediction engine built on alternative data. That ground is taken, since one property-data firm already sells catchment analysis across 182,000+ projects[4]. So this version narrows it to one decision that has no good tool - should I trust this tenant?
Lesseewise takes a tenant's name and address and builds a report. It checks company status and filings, whether its tax registration is active and returns are filed, how many outlets the brand opened or shut in the past year, and whether its review count and ratings are sliding. A model reads these together and gives a plain-language risk band, with every signal shown so the buyer can judge for themselves. After purchase it sends an alert when something changes, like a store closure or a lapsed registration.
Reports cover businesses, not individuals. Where a tenant is a sole proprietor, the report sticks to business records.
The user is the investor, say a doctor, business owner or NRI buying a ₹1–5 Cr shop. The payer is often the broker or wealth adviser who brought the deal, because a report helps close it. Small property funds and SM REIT managers, which buy pre-leased assets[5], are a second buyer for portfolio monitoring. There's no public price for this kind of report in India, so pricing needs testing.
High-street leasing is rising while malls lose tenants[2], so more single-tenant shops are being sold to individuals. Seven SM REITs have registered with SEBI since August 2024[5], each buying pre-leased assets and needing tenant checks. Office vacancy turned up in Q3 2026 for the first time in twelve quarters[3].
There's no public figure for pre-leased property sales to individuals in India. The firmest signals are the 2.22 msf of retail leasing in Q3 2026 across eight cities[2] and the seven SM REITs on SEBI's register[5]. Treat the ghost-mall data[1] as context on tenant risk, not as a market size.
Property-data firms serve developers, lenders and REITs with project and catchment data[4], not tenant monitoring. Credit bureaus sell commercial reports to lenders, but small investors rarely see them. Brokers check tenants informally over a phone call.
The gap is a cheap report that an individual can read and that keeps watching after the sale.
| Difficulty | Moderate (37/100) |
| Starting capital | ₹50–90 L |
| Time to launch | 5–8 months |
The data work is fiddly, and matching a tenant's trading name to the right company and outlets takes care. Selling is harder. Brokers love reports that help close deals and hate ones that kill them, so the report has to feel fair to both sides.
No licence is needed to sell tenant reports on properties investors buy directly. The limits come from data and securities rules.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't treat the risk band as a buy or sell decision. Public data has gaps and lags, and the investor should still read the lease and meet the tenant.
Want to work out the AI layer for Lesseewise? Talk to Yash →
I think this is a fair bet for a founder who knows commercial brokerage or credit risk and can build data pipelines cheaply. If you're hoping to predict prices across a whole city then this isn't your idea. First prove that brokers or funds will pay for 30 reports in a month, and that two of those reports changed a decision.
Plan for roughly ₹50–90 L, mostly for data collection, the model and a small analyst team.
Not for reports on property investors buy directly. Avoid rating SM REIT units for retail investors, and follow the DPDP Act for sole-proprietor data.
Yes, wherever pre-leased property is bought by individuals. Check what company and tax data is public there and your own data protection law.
The free Lesseewise validation kit has the line-by-line capital breakdown, the effort scoring, a rules checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for investors and brokers, and 5 assumptions to test. Download the kit →
Thinking about building Lesseewise or something close to it? The make-or-break work is getting brokers to share reports that might slow their own deals, which is a tricky sell but not an impossible one. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.