Running tally of sanctioned floor area against each TOD zone's planned limits
TL;DR Headroomly gives a development authority a 3D model of each transit zone or planning ward that grows with every building plan it sanctions. Planners see how much of the zone's planned floor area, population and service capacity is already used. Authorities and metro TOD cells pay a yearly fee, and the case rests on denser zoning rules needing evidence.
Cities are raising permitted density around metro stations. National guidance puts the floor area ratio in these zones at 300–500% or more, within roughly an 800-metre walk of a station[1]. Delhi's draft TOD rules ask planners to assess the extra load on roads, water and services in each influence zone, and they make every project file a traffic and services study[2].
Each study looks at one scheme, and nobody is required to add them up. Meanwhile the national programme that paid for digital master plans covered 461 towns, with drafts ready for 283 and final plans for 148 at the time of a 2022 ministry presentation[3]. Those plans are static layers. Once a plan is notified, sanctioned buildings rarely flow back into it. I couldn't find a single public study of how far approvals have outrun planned capacity in any zone.
The seed pitched an AI city twin to cut planning delays. That's broad, and an Indian vendor already sells per-plan scrutiny to authorities[4]. I narrowed it to the question no current tool in India answers - how much room is left in this zone?
Headroomly loads the authority's master plan or zonal plan, its development rules and the planned capacity figures behind them. Then it pulls every sanctioned plan from the online permission system as a simple block with footprint, floors, built-up area, use and dwelling units. Premium floor area bought under TOD rules goes in too. What you get is a 3D model of each zone with a meter beside it showing planned floor area, what's sanctioned so far, what's built and what remains for water, sewer and parking demand.
When a big proposal arrives the planner sees the zone's position before and after it. When the plan comes up for revision the department has years of actual uptake to work from instead of estimates.
Scope: decision support for planners only. It never grants or refuses a permission, and the statutory process stays as it is.
The users are town planners and TOD cells. The payers are development authorities, municipal planning departments and metro companies that collect premium floor-area charges. Buying runs through tenders or the government marketplace. I found no public Indian price for a comparable subscription, so test ₹15–40 lakh a year per authority, including setup and rule coding.
Higher TOD density is moving from policy into notified rules, and Delhi's draft ring-fences the premium charges in a fund for the zone's infrastructure[2]. That creates a buyer with money and a reason to track uptake. Most AMRUT towns now hold a GIS base map at 1:4,000[3], so the base layer is already there.
There's no public figure for what Indian authorities spend on planning software. The nearest signal is adjacent - the GIS master plan sub-scheme carried a ₹515 crore outlay across 461 towns[3]. That money built maps and plans, not ongoing tracking. Treat it as proof that authorities fund digital planning, not as your market.
One Indian plan-check product checks individual drawings and BIM models against local codes before submission[4], one plan at a time. A global GIS vendor's urban planning tool is the closest product. It stores zoning rules, shows 3D envelopes and compares scenarios[5], but Indian rule packs and permission-system links are left to the buyer. A listed Indian mapping company sells 3D city twin products[6], aimed at mapping rather than an approvals ledger. The gap is a ledger tied to Indian sanction data.
| Difficulty | Moderate (47/100) |
| Starting capital | ₹1.2–2.2 Cr |
| Time to launch | 9–12 months |
The software is manageable. Data and selling are the hard parts. Sanctioned plans sit in permission systems run by other vendors, so access depends on the authority's goodwill, and planned capacity figures are often buried deep in plan reports. Government sales cycles can outlast a seed round, which is not a fun thing to discover halfway through.
No sector licence is needed to run this. The product supports planners and never issues a permission, so the baseline applies.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't let AI decide whether a proposal fits. Extracted figures need a human check, and the sanction decision stays with the authority.
Want to work out the AI layer for Headroomly? Talk to Yash →
I think this suits a founder with urban planning or government GIS experience and the patience for tenders. If you're expecting quick self-serve sales then it's a poor fit. First prove that one authority will hand over two years of sanction data, and that its planners use the meter in a real approval or revision discussion.
My estimate is ₹1.2–2.2 Cr, mostly for GIS engineering, data loading for the first authority and a long tender cycle. The kit breaks it down.
No sector licence applies, because the tool supports planners and never grants permissions. You'll still need GST, a data-processing agreement under the DPDP Act and the paperwork tenders ask for.
Yes, the logic works anywhere a city caps floor area by zone. Check how your local planning law and data rules treat sanction records first.
The free Headroomly validation kit has the line-by-line capital breakdown, the effort scoring, the procurement and data checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for planners and TOD cells, and 5 assumptions to test. Download the kit →
Thinking about building Headroomly or something close to it? The make-or-break work is getting sanction data out of a permission system you don't run, and I'm happy to help you plan that approach. 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.