Scores land for low-income housing by how easily residents can reach jobs
TL;DR Plotmetric scores candidate land parcels for affordable and mixed-income housing by travel time to jobs, transit, schools and clinics. Housing boards, development authorities and builders pay per study or per year. The point is simple - stop building low-income homes where nobody can afford to live.
India has built and sanctioned low-cost homes at scale, 127.68 lakh under PMAY (Urban), of which 99.07 lakh are complete[1]. Location is the weak link.
The new PMAY-U 2.0 guidelines include a whole model for renting out government-funded houses that were built under earlier schemes and still lie vacant[2]. That fix only exists because a lot of those homes went up where people didn't want to live.
The last official estimate put the urban shortage at 18.78 million households, almost all of them lower-income[3]. Yet the 2011 Census counted about 1.1 crore vacant urban homes[4]. Homes far from work stay empty while the shortage carries on, which is a sad mismatch.
The seed pitched AI site selection plus virtual-reality sessions with neighbours. We kept the first half and dropped the second. We found no buyer in India for VR consultation, and it doesn't solve the location problem anyway.
Plotmetric takes a list of candidate parcels from a housing board or builder. For each one it measures travel time by bus, metro and walking to the clusters of jobs that low-income workers hold, such as industrial estates, markets and hospitals. It adds distance to schools, clinics and water supply, and flags parcels inside the new affordable housing zones that states are asked to map[2]. What comes out is a ranked shortlist with a one-page reason for each parcel.
For builders, the same scores help place the 5% of built-up area that states must now reserve for lower-income homes in large projects[2].
State housing boards, development authorities and urban local bodies pay per study or through an annual licence, bought by tender. Builders with large projects pay per site. The people who actually benefit are lower-income buyers and tenants, and they never see the product. We found no public price for comparable site studies in India, since consultants usually bundle them into project reports.
PMAY-U 2.0, launched in September 2024, asks states to add affordable housing zones to master plans, map land banks for partnership housing and reserve 5% of large projects for lower-income homes[2]. Each of those steps needs a reasoned choice of land. The scheme also targets 1 crore families over five years[2], so a lot more parcels are about to be picked.
Nobody publishes a figure for spending on housing site analysis in India. The narrowest anchor is the pipeline. PMAY-U 2.0 aims to support 1 crore urban families[2], and every partnership or rental project needs a site.
The neighbour is in the US, where one firm sells site and community data to utilities, banks and governments[5]. That shows public buyers will pay for this kind of analysis.
US data firms sell climate, community and built-environment data for site selection in the US[5]. Plan-checking software checks building plans against zoning rules for councils and developers[6], but it answers whether a building fits a site and not whether people will want to live there. In India, planning consultants do site studies by hand for each project.
We found no product that ranks parcels by job access for low-income housing. That's the gap.
| Difficulty | Moderate (41/100) |
| Starting capital | ₹60 L–1.2 Cr |
| Time to launch | 6–9 months |
The travel-time maths is well known. Data and selling are the hard parts. Job locations for informal workers are patchy, and bus routes in smaller cities are rarely published in a form you can use. Public buyers move through tenders, pay late and want reports that survive audits.
No special licence is needed to sell site analysis. US site-data vendors sell to governments without one[5]. So the list is mostly the baseline:
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't let AI make the final siting decision. Data on informal jobs and transport is patchy, and a planner needs to check every shortlist on the ground.
Want to work out the AI layer for Plotmetric? Talk to Yash →
Here's what can go south -
I'd say this is worth trying for a founder with GIS or transport-planning skills and real patience for public buyers. If you need revenue in six months then skip it.
Prove one thing first - that your scores predict reality. Rank 20 completed projects and show that the low scorers are the ones with empty homes.
Plan for roughly ₹60 L–1.2 Cr, mostly for a GIS team, data and a long public sales cycle.
No sector licence. You need the usual company, GST and Shops and Establishments registrations, and public sales go through tenders or the Government e Marketplace.
Yes, US firms already sell similar tools to governments. Check local procurement rules and open transport data before you start.
The free Plotmetric validation kit has the line-by-line capital breakdown, the effort scoring, the data and procurement checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for housing boards and builders, and 5 assumptions to test. Download the kit →
Thinking about building Plotmetric or something close to it? The make-or-break work is proving your scores match real occupancy on projects already built, and I'm happy to help you test that. 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.