The AI-powered, human-in-the-loop platform that tells drivers exactly where to park — indoors, where GPS goes dark.
Every indoor environment — a mall, an airport, a hospital — becomes as searchable and navigable as the street outside it. ParkMyCar starts with the highest-friction indoor problem — parking — and builds the data layer for everything indoors that comes after.
Once a driver enters a parking structure, every map on their phone goes blind.
average time wasted circling for a spot in a busy mall or airport
typical CAPEX for a sensor- or camera-based system per facility
of today's consumer map apps route you to an indoor parking spot
| TAM — Total Addressable Market. Top-down: the global indoor positioning & navigation market, all applications, all verticals, all geographies. | AED 38B |
| SAM — Serviceable Addressable Market. Bottom-up: ~155,000 target facilities worldwide (malls 50,000; airports 4,000; hospitals 30,000; campuses 25,000) × a blended ARPU of ~AED 19K–25K/year, filtered to the navigation/wayfinding sub-segment (~a quarter of the total category). | AED 9.2B |
| Region | Malls | Hospitals | Airports | Campuses | Rough total |
|---|---|---|---|---|---|
| GCC (UAE, Saudi, Qatar, etc.) | ~700 | ~2,000 | ~50 | ~500 | ~3,250 |
| South Asia (India, Pakistan, Bangladesh) | ~2,500 | ~5,000 | ~150 | ~3,000 | ~10,650 |
| Combined SOM | AED 410M | ||||
TAM → SAM → SOM, illustrative sizing based on public smart-parking and PropTech market research.
On-site staff confirm spot status in seconds through a simple app — no drilling, no cameras, no CAPEX.
No hardware install — onboard a facility with a mobile app and a walk-through, not a construction crew.
Comparatively low cost for the setup.
Every human confirmation is a labeled training example for the underlying AI model.
Human verification means occupancy data is trustworthy immediately — not after months of tuning.
A smooth guided journey for the user.
Driver opens the app on arrival at the facility.
App routes to the nearest confirmed-vacant spot.
Spot is marked occupied the moment they pull in.
Exact level, row and spot saved automatically.
One tap walks them straight back to their car.
A lightweight task for on-site staff — minutes of extra work, in exchange for a commission and a live occupancy feed.
Staff walk an assigned zone as part of a normal round.
Confirm each spot's status in the ParkMyCar staff app.
Status syncs instantly to the live occupancy model.
Drivers see accurate, up-to-the-minute availability.
Every human confirmation flows down into training data; every AI prediction flows back up as a faster, cheaper way to serve the next request.
Every confirmed spot and staff check-in feeds one continuously updating occupancy model per facility — the foundation for parking today, and full indoor wayfinding tomorrow.
Every floor and zone tracked independently, in real time.
Each spot carries a freshness and confidence score, not just a status.
Utilization patterns over time power forecasting and planning.
Staff confirm every spot manually. 100% accurate, zero model dependency.
Model proposes status; staff confirm only low-confidence spots.
Pricing scales with facility size and analytics depth — figures below are illustrative and will be validated in pilots.
Gross margin at scale
Revenue streams
Payback period, target
Time to deploy per facility
The core cost is the per-spot fee paid to on-site staff for every confirmed reservation — it scales linearly with facility count and market penetration, nothing else.
| Y1 | Y2 | Y3 | Y4 | Y5 | |
|---|---|---|---|---|---|
| Facilities | 4 | 16 | 50 | 100 | 200 |
| % Target | 25% | 25% | 35% | 45% | 50% |
| Daily Cost (AED) | 800 | 3,200 | 14,000 | 36,000 | 80,000 |
| Yearly Cost (AED) | 288K | 1.15M | 5.04M | 12.96M | 28.80M |
Cost scales predictably with growth — no fixed infrastructure, hardware, or facility CAPEX in the model.
Phase 1 streams are live from launch; Phase 2 streams switch on once the platform reaches multi-facility scale (Year 3+).
Ad and offer revenue scales with the same driver as facility cost — daily car volume — which is why it dominates the mix as facilities scale.
80%
11%
8%
1%
Revenue outpaces cost every year in this model — net profit grows ~17x from Year 1 to Year 5, though margin compresses as the cost base scales with facility footprint.
| Details | Y1 | Y2 | Y3 | Y4 | Y5 |
|---|---|---|---|---|---|
| Total Revenue (AED) | 590,284 | 2,361,136 | 8,435,270 | 16,999,980 | 34,129,400 |
| Total Cost (AED) | 288,000 | 1,152,000 | 5,040,000 | 12,960,000 | 28,800,000 |
| Net Profit (AED) | 302,284 | 1,209,136 | 3,395,270 | 4,039,980 | 5,329,400 |
| Margin | 51.20% | 51.20% | 40.30% | 23.80% | 15.60% |
Figures sourced from the ParkMyCar costing model — bottom-up, formula-driven, and denominated in AED.
A focused, three-step GTM starting with the highest-density mall market in the region.
3–5 flagship Dubai & Abu Dhabi malls as design partners.
Co-sell through mall management and facilities companies.
Use pilot data to expand across the GCC mall portfolio.
High-value long-stay parking with premium spot reservation.
Time-critical parking for patients, visitors, and staff shifts.
Loading-dock and fleet-bay occupancy for logistics operators.
Municipal parking structures as part of city-wide mobility data.