GharPulse, a Lahore-based PropTech startup, is building the first block-level property price intelligence in Pakistan. It scrapes, cleans, and analyzes over 8,000 active listings across 21 Lahore societies to publish Low, Mid, and High price bands for homes, plots, and commercial property, a reference point that Pakistan’s Rs 90 trillion real estate market has never had.
Pakistan’s property market runs on asking prices. A seller lists on Zameen.com. A buyer calls an agent. Neither has a standardized way to check what the property is actually worth against comparable listings in the same block. In a market the Overseas Investors Chamber of Commerce and Industry (OICCI) values at Rs 90 trillion, that information gap is anything but small.
GharPulse has produced nearly 2,000 assessment data points so far. But the technically interesting part is not the collection. It is what happens between the raw listing and the published assessment. Here is how the pipeline works.
GharPulse at a glance
| What it is | Property intelligence platform producing block-level price assessments |
| Based in | Lahore, Pakistan (founded 2026, SECP and FBR registered) |
| Coverage | 8,000+ active listings across 21 Lahore societies |
| Output | Low / Mid / High asking-price bands per location, category, and size |
| Data source | Asking prices scraped from major Pakistani property portals |
| Products | Price Check, Analytics Dashboard, Marketplace with assessment badges, Interactive Maps |
| Next cities | Karachi and Islamabad |
| Website | gharpulse.com |
The problem: a Rs 90 trillion market with no price reference
Pakistan has no mandatory transaction price disclosure. That single fact shapes everything about how property is bought and sold. Sale prices stay private, so the only public signal is the asking price a seller chooses to publish.
Asking prices are noisy. The same 10-marla plot can be listed at three different prices on three portals by three agents. Buyers negotiate against rumors and neighbors’ anecdotes. Banks, REITs, and mortgage schemes all need valuations, and none of them have a consistent public benchmark to anchor on.
This is the gap GharPulse is building data infrastructure to close, starting with Lahore.
How the GharPulse data pipeline works
GharPulse runs a proprietary scraping engine across Pakistan’s major property portals. The hard part is not scraping. It is data quality.
A single property often appears on multiple portals with different addresses, sizes, and prices. Society names are not standardized either: DHA Phase 6 might be listed as “DHA Ph 6,” “Defence Phase VI,” or “DHA Lahore Phase 6 Block D.” Before any analysis begins, every listing passes through a normalization layer:
- Clean: strip formatting noise, unify units, and parse prices consistently.
- Deduplicate: merge the same property listed across portals or by multiple agents.
- Map to a location hierarchy: City → Society → Phase/Sector → Block.
- Normalize to a standard schema: location, category (Homes, Plots, Commercial), size (marlas or kanals), and asking price.
- Exclude the unmappable: any listing that cannot be reliably tied to a specific block is dropped.
The last step is a deliberate design choice. In GharPulse’s view, an inaccurate data point is worse than a missing one.
The GharPulse Assessment Engine: Low, Mid, and High price bands
The assessment engine turns normalized listings into three price bands for every combination of location, category, and size. It works at the block level because that is how the Pakistani market actually prices property. A 10-marla plot in DHA Phase 6 Block D commands a different price than one in Block J.
Factors that separate blocks include proximity to commercial areas, park-facing positioning, corner versus mid-row placement, and access roads.
| Band | What it captures |
|---|---|
| Low | The lower end of asking prices: motivated sellers, less desirable positioning |
| Mid | The central tendency of the market for that block, category, and size |
| High | Premium listings: corner plots, park-facing, newly constructed |
Together, the three bands give buyers, sellers, and lenders the first objective reference point the market has had.
Is GharPulse the Zillow of Pakistan?
Not quite, and the platform is transparent about why. Zillow’s Zestimate is built on actual transaction data. Pakistan has no mandatory transaction price disclosure, so GharPulse builds its assessments from asking prices instead.
| Zillow (US) | GharPulse (Pakistan) | |
|---|---|---|
| Data source | Recorded sale transactions | Published asking prices |
| Output | Single estimated value | Low / Mid / High band |
| Granularity | Individual property | Block × category × size |
| Represents | Likely sale price | Market expectations |
The distinction matters. A GharPulse band tells you what sellers in a block are asking, not what buyers have paid. But in a market where no public reference existed at all, asking-price intelligence at the block level is a meaningful first step. The closer international comparison is HouseSigma in Canada, which also started by layering analytics over listings data.
Tech stack, storage, and the data moat
GharPulse stores assessments in structured PostgreSQL tables via Supabase and delivers them through a modern React stack.
| Layer | Technology |
|---|---|
| Frontend | TanStack Start (React SSR), TypeScript, Tailwind CSS |
| Database | PostgreSQL via Supabase |
| Maps | Leaflet.js with OpenStreetMap, price-band overlays per block |
| Deployment | Lovable and Cloudflare |
| Source code | github.com/gharpulse/ghar-pulse-pakistan |
The architecture is designed for compounding data. Every scraping cycle adds points, and assessments recalculate as new listings enter. Over time this creates a historical price-trend layer that Pakistan’s property market currently lacks, and one that is expensive and slow for a competitor to replicate from scratch. The dataset deepens daily; that is the moat.
Why block-level data matters for Pakistan’s PropTech ecosystem
GharPulse’s timing coincides with a formalization wave in Pakistani real estate, and every piece of it depends on reliable valuations.
- REIT reform: SECP’s September 2026 amendments allow investment-based REITs to hold vacant land for the first time. Land held in a REIT needs a defensible price.
- Tokenization: Fasset hit unicorn status in August 2026 and is tokenizing Pakistani real estate through its partnership with Habib Rafiq Limited. Fractional ownership needs a reference value per unit.
- Subsidized mortgages: the “Mera Ghar, Mera Ashiana” scheme offers subsidized home financing. Lenders need a benchmark to underwrite against.
If platforms producing block-level intelligence from market data are treated as infrastructure rather than experiments, Pakistan’s Rs 90 trillion real estate market gets the information layer that each of these reforms currently depends on.
What’s next for GharPulse
GharPulse currently covers 21 societies across Lahore, with Karachi and Islamabad planned next. The platform today offers four products:
- Price Check: block-level Low / Mid / High assessments for a specific property type and size.
- Analytics Dashboard: trends across societies and categories.
- Marketplace: listings carrying a GharPulse Assessment badge.
- Interactive Maps: Leaflet-based maps with price-band overlays per block.
For the broader PropTech ecosystem, the signal is clear: the data problem in Pakistani real estate is solvable. The tools exist. The listings data exists. What was missing was the pipeline to turn raw listings into decision-grade intelligence. GharPulse has built that pipeline for one city. The open question is how fast it scales to the rest of the country.
Frequently asked questions
What is GharPulse?
GharPulse is a Lahore-based property intelligence platform that tracks 8,000+ active listings across 21 societies and produces block-level price assessments for homes, plots, and commercial property in Pakistan.
How does GharPulse calculate property prices?
GharPulse scrapes major Pakistani property portals, normalizes each listing to a City > Society > Phase > Block hierarchy, and produces Low, Mid, and High asking-price bands for every combination of location, category, and property size.
Is GharPulse the same as Zillow?
No. Zillow’s Zestimate uses recorded sale transactions. Pakistan has no mandatory transaction price disclosure, so GharPulse builds its bands from asking prices. Its assessments represent market expectations rather than completed sales, closer to HouseSigma in Canada than to Zillow.
Which cities does GharPulse cover?
GharPulse currently covers 21 societies across Lahore. Karachi and Islamabad are planned next.
What tech stack does GharPulse use?
TanStack Start (React SSR), TypeScript, Tailwind CSS, PostgreSQL via Supabase, Leaflet.js with OpenStreetMap, deployed through Lovable and Cloudflare. The source code is on GitHub.
Is GharPulse free to use?
The platform offers Price Check assessments, an Analytics Dashboard, a Marketplace, and Interactive Maps at gharpulse.com. (Editor: confirm pricing with GharPulse before publishing; not stated in the source.)
About GharPulse
GharPulse (Pvt.) Ltd. is a property intelligence platform based in Lahore, Pakistan. Founded in 2026, it produces block-level price assessments using proprietary data aggregation across Pakistan’s major residential societies. The company is SECP and FBR registered.
Website: gharpulse.com · Contact: contact@gharpulse.com · YouTube: @GharPulse · Instagram: @gharpulse