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Premium Property Discovery App services

Find Me Home β€”
Building a Property Discovery App That Actually Matches What Buyers Want

A startup's vision of stress-free property hunting β€” built into a fully coordinated iOS and Android platform helping buyers search, compare, and connect with agents without wading through irrelevant listings.

Premium Property Discovery App services

Industry

Enterprise Project Management
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Business Type

Startup
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Project duration

4 Months
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Premium Property Discovery App services Premium Property Discovery App services

About Client

Find Me Home was built around a frustration most property hunters know well: you open a listings app, filter by location and price, and still end up scrolling past dozens of homes that don't actually match what you're looking for, with photos too thin to tell you anything real. The client's question was whether a single app could make property search feel genuinely precise β€” filtering not just by price and location, but by size and amenities too, with listings detailed enough that a buyer could shortlist a home without ever leaving the app.

Their answer was one connected platform. Buyers search using layered filters, view listings with photos, virtual tours, and floor plans, save homes they like, and contact agents directly. The admin team manages listings, users, and support from a single Laravel panel.

About Client Gmta

Why Find Me Home Chose Us

Manage MyWork GMTA

Property search apps look simple on the surface, but the filtering and matching logic underneath is a different kind of engineering problem than a basic listings feed. Find Me Home needed layered search across location, price, size, and amenities working together, saved-search notifications that actually matched new listings correctly, and rich listing detail β€” virtual tours and floor plans β€” loading fast enough not to frustrate a buyer mid-search.

The client had looked at generic real estate app templates and found filtering shallow, saved-search notifications unreliable, and no structured way to manage agent contact requests or listing ads from one place. There was no admin system built to handle usage analytics, listing moderation, and support requests together, and no reviews system tied cleanly to individual properties and agents. These were product requirements that needed a custom build.

Find Me Home
Find Me Home
Find Me Home
Find Me Home
Find Me Home
Find Me Home

Challenges That Shaped the Build

01 06

Building a Property Search or Real Estate Platform?

Layered search, rich listing media, and saved-search accuracy all need to work together, not as separate features bolted onto a generic listings feed.

music App Like Manage MyWork? 6 Months Free Maintenance After Launch
Find Me Home

Our Approach

Combined Filter Search Built for Precision

Combined Filter Search Built for Precision

Rather than treating location, price, size, and amenities as separate filters applied one after another, we built the search engine to evaluate all four together against the listing database in a single query. This meant a buyer narrowing by neighbourhood, then price range, then bedroom count, saw results update accurately at every step rather than a broad list that only tightened at the very end. We indexed the database specifically around these combined filter patterns, since the most common searches layer several criteria at once rather than searching on a single attribute in isolation.

01
Progressive Media Loading for Rich Listings 02

Progressive Media Loading for Rich Listings

Every listing page loads photos first, since that's what a buyer scans initially, while virtual tours and floor plans load in behind them without blocking the page or making the buyer wait. This structure meant a listing felt fast even when it carried genuinely heavy media, because the buyer was already looking at photos by the time the heavier content finished loading in the background. We treated perceived speed as seriously as actual load time, since a buyer scrolling quickly through listings notices a stall far more than a few extra seconds of total load time.

Precise Saved-Search Matching 03

Precise Saved-Search Matching

Every new listing added to the platform gets checked against every active saved search, rather than relying on a broad category match that could easily misfire. We built this matching logic to evaluate the same combined criteria β€” location, price, size, amenities β€” that the buyer originally used to save the search, so a notification only fires when a listing genuinely qualifies. This approach significantly reduced irrelevant alerts while ensuring buyers received timely notifications for genuinely relevant properties.

In-App Agent Contact With Full Conversation Tracking

In-App Agent Contact With Full Conversation Tracking

Buyer-agent communication runs through the app itself rather than exposing raw phone numbers or email addresses on a public listing page. This protects agents from open spam while giving buyers a clear, trackable conversation history tied to the specific property they inquired about. The admin panel surfaces these conversations too, giving the operations team visibility into how buyers are engaging with listings and where agents might be slow to respond, without needing to ask either side directly, improving response quality and operational decision-making efficiency.

04
Streaming Pipeline Built for Stability

Process We Followed

01 Discovery and Search Architecture Discovery and Search Architecture
Discovery and Search Architecture

Discovery and Search Architecture

Before development began, we mapped how location, price, size, and amenities needed to combine within the search engine, defined the saved-search matching logic, and designed the listing pages around progressive media loading from the outset. Every search and listing workflow was validated before development to ensure fast, relevant, and consistent property discovery from day one.

  • Combined filter logic mapped across all search attributes
  • Saved-search matching criteria defined
  • Listing page and admin panel wireframes
  • API contract and database indexing strategy
02 Core Development β€” Apps and Admin Panel Core Development β€” Apps and Admin Panel
Core Development β€” Apps and Admin Panel

Core Development β€” Apps and Admin Panel

The customer app, admin panel, and backend were developed concurrently, with combined search filtering, progressive media loading, and in-app agent contact built in parallel rather than sequentially, to keep listing accuracy consistent from the start.This parallel development approach ensured every feature remained fully aligned across all platforms from the first release.

  • Combined filter search engine built into core query logic
  • Progressive media loading implemented for listing pages
  • Admin panel built as a first-class product β€” listings, ads, and support
  • iOS Swift and Android apps integrated against the same backend
03 QA, Matching Accuracy Testing, and Launch QA, Matching Accuracy Testing, and Launch
QA, Matching Accuracy Testing, and Launch

QA, Matching Accuracy Testing, and Launch

All listings and saved searches were tested against filter combination accuracy, notification matching precision, and media load performance before submission to the App Store and Google Play. Cross-platform testing also confirmed consistent search behavior and listing presentation across all supported devices and screen sizes.

  • Combined filter accuracy testing across search attributes
  • Saved-search notification matching testing at scale
  • Listing media load performance testing across device types
  • Launch across iOS, Android, and the web admin panel

Business Impact

Combined Search Filters 4

Combined Search Filters

Location, price, size, and amenities all narrow results together in a single search, not as separate sequential steps.

Average Listing Load Time 2sec

Average Listing Load Time

Progressive media loading keeps listing pages feeling fast even with photos, virtual tours, and floor plans included.

Saved-Search Match Accuracy 90%

Saved-Search Match Accuracy

Notifications fire almost exclusively for listings that genuinely match a buyer's saved search criteria, cutting irrelevant alerts significantly.

Sazpay Sazpay

Ready to Build a Smarter Property Discovery App?

From combined search filters to in-app agent contact, we build real estate platforms designed around how buyers actually search.

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GMTA's flexible approach and prompt replies to client enquiries are among their business's assets. They have an excellent team of marketers and developers that are up to date on the latest technology and business trends.

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GMTA Software Solutions did a really great job managing my E-learning app's development. The product is seamless and has helped me boost my business in the global market. Highly recommended!

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GMTA have been a reliable partner for our project both from an analysis perspective to development and roll-out. The team has great knowledge of the service they were delivering.

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GMTA Software developed my Tokyo MK app superbly. They understood my needs, used the latest tech, and delivered on time. Highly recommend for great app development service.

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