Custom Feature for Real Estate Webapp

@mascotindia123

Hello, I have carefully read your complete requirements, and it would be an honor to work with you. With 14+ years of experience in full-stack development, backend APIs, web scraping, and Supabase integrations, I can build the backend service to extract listing data, integrate with authorized third-party data sources, and expose a clean API for your Lovable frontend. I will develop a secure, scalable solution with robust matching logic, well-documented endpoints, and seamless integration while respecting the terms of the data sources used. Please check my profile to see my reviews and ratings from previous clients. I am committed to delivering a reliable, production-ready solution with regular progress updates throughout the project. Budget and timeline can be discussed further. Warm regards, Harpreet Singh

@KESHAVINFOTECH

Hi, This feature has two critical parts: reliably extracting listing data from the portal and matching it to the correct unit with high confidence before any owner data is returned. I’d build it with a fail-safe approach so results are only shown when the match is strong. My focus would be on the backend flow: accepting the portal URL, extracting and normalizing listing attributes, then comparing them against DLD or third-party records through a structured matching layer. I can also expose a simple API or Supabase Edge Function for your Lovable app, with logging and clear error states for unmatched listings. Relevant work would include: URL input and listing parsing Data normalization and unit matching API / Edge Function endpoint Frontend response formatting Testing with real listing samples I can review this further through Freelancer chat or video call, available 11 AM–8 PM IST. One quick question: do you already have access to the DLD or third-party database/API, or should I build around the source you plan to use? Regards, Ghanu & Samir KESHAV INFOTECH

@ahmadayaz

I specialize in backend development and API integrations, having successfully implemented similar custom features. I use advanced web scraping techniques and database querying to extract data accurately. I can integrate with Dubai Land Department and real estate databases, ensuring secure and efficient data extraction. My experience includes developing API endpoints with Supabase for optimal performance. Let's discuss how to enhance user experience and data accuracy for your real estate webapp.

@kamran2012

Hi, I will build the backend that takes a Bayut or Property Finder URL, scrapes the listing details, and matches them against DLD transaction data to return the unit number, owner name, and phone number through a Supabase Edge Function your Lovable frontend can call directly. On a similar project, rotating proxy headers and fingerprint randomization kept portal scraping stable for months without blocks. Questions: 1) Do you already have access to a DLD transaction dataset or a third party API like DataFinder, or do I need to source that? 2) Should the matching logic handle off plan units, or only completed/transferred properties? Share one example listing URL and I will confirm what data points each portal exposes before we scope the matcher. Kamran

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a Custom Real Estate Tool for Data Extraction and API Integration ❇️ Hi My Friend, I hope you are doing well. I've reviewed your project requirements and noticed you're looking for a backend developer with API expertise. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for real estate web applications. I will create a tool that efficiently extracts data from property listing URLs and integrates it seamlessly into your Lovable frontend. ➡️ Why Me? I can easily build your custom feature as I have 5 years of experience in backend development and API integration. My expertise includes web scraping, data extraction, and database management. Additionally, I have a strong grip on technologies like Python, Node.js, and various databases, ensuring a robust solution for your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ Backend Development ✅ API Integration ✅ Web Scraping ✅ Data Extraction ✅ Database Management ✅ Python ✅ Node.js ✅ JavaScript ✅ Data Analysis ✅ Error Handling ✅ RESTful Services ✅ Supabase Functions Waiting for your response! Best Regards, Zohaib

@KatrinaQ

Hi, I'm a senior developer with 20+ years of experience building scraping, API, and database systems, and I've delivered similar real estate data extraction solutions before. I'll set up a backend service that first extracts the listing details from the portal URL, then queries the DLD database or third-party provider to match the unit, and finally retrieves the owner's contact information. To avoid scraping blocks, I'll implement rotating user agents, delays, and proxy rotation, while keeping the API endpoint clean and efficient for your Lovable frontend integration. I'll test the matching accuracy and handle edge cases like missing data or portal changes. I can start immediately.

@onkarkulkarni8

Hi, I can help with your "Custom Feature for Real Estate Webapp" project. I build clean, maintainable PHP backends — core PHP and Laravel/Symfony, MySQL schema design, and well-structured REST APIs. For work involving php, javascript, mobile app development, web scraping, database development, data extraction, backend development, api development, I pay close attention to validation, security, and readable code, delivering in small, testable milestones. I provide clean commits and clear documentation. Can we discuss the specifics before I firm up the timeline? ⭐ 5.0/5 from a recent client: "it was great working with him, did whatever changes i asked him as per my need." Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@DeveloperStation

Hi, I've spent 15 years building backend and API systems, and as CTO I've led development of 50+ products, including scraping pipelines and Supabase edge functions. One thing worth flagging early: the scraping side of Bayut and Property Finder is the easy half. The hard part is the owner data. DLD transaction history does not expose owner phone numbers through any legitimate API I know of, so those Telegram bots run on grey-market data sources. Can you tell me which specific database or API you plan to use for owner lookup? That decides whether this is buildable as described. For scraping I'd use rotating proxies and headless requests behind a queue, returning clean JSON to your Lovable frontend. I'd suggest starting with a small milestone on the listing extraction endpoint so you only pay on working output. Which portal should I target first? Adil

@C0RETECHIES

Hi there, I understand you need a backend microservice for your Lovable app. The workflow is clear: your frontend will send a property portal URL to our API. The service will then scrape key details (building, size, layout), use this data as a fingerprint to query a DLD or similar database to uniquely identify the unit, and return the owner's name and phone number. Technical approach: We'll build this as a Node.js microservice, deployable as a Supabase Edge Function. For scraping, we will use a headless browser with rotating residential proxies and user-agent cycling to manage portal blocks. The core logic will query your specified real estate database API to match the unit and retrieve owner data, which a simple REST API endpoint will serve to your Lovable app. Core modules: 1. Scraping Engine: Parses property details from portal URLs. 2. Matching Engine: Queries the external database to find the unique owner record. 3. API Layer: Handles requests and returns the final contact data. Relevant systems: Our 'Automation Lead Generator' system has a similar operational flow. It performs multi-source data enrichment and contact discovery by integrating with various external APIs to build a complete profile from an initial data point. We’ll start by building and testing the scraper for one portal, then integrate the database matching logic before exposing the final API endpoint for your integration. This validates the core functionality quickly. Regards, Rohit

@giaphung2k1

Hello Building a real estate webapp usually stalls around map performance and syncing property data smoothly. Having recently built a similar platform where I optimized interactive map searches to load in under 1.5 seconds, I can ensure your users get a fast, lag-free search experience. Could you share the specific tech stack you're using? I would love to send over a quick video demo of my previous real estate work. Giáp Văn Hưng

@teodorgeorge

Hello, I have worked on backend API flows for real estate tools that extract listing data, match records, and return structured results to a frontend. Your Lovable app needs careful handling of portal URLs, listing details like building, price, size, bedrooms, and matching against DLD or a licensed data source. I would build the scraping and parsing layer, then add matching logic to isolate the unit and return owner data through a clean API or Supabase Edge Function. For scraping blocks, I would use compliant methods such as official APIs, stable third-party data providers, rate limits, and resilient parsing. Best regards, Teo

@mahig47

Hello! As per your project post, you are looking to extend your existing Lovable based real estate web application with a custom backend feature that automatically extracts property details from listing URLs, matches the property with external real estate records, and returns the associated owner information through a secure API that integrates seamlessly with your existing frontend. My focus will be on developing the complete backend workflow including property listing data extraction, intelligent data parsing, third party API integration, database matching logic, Supabase Edge Functions or REST API development, secure backend architecture, error handling, logging, rate limiting, API response optimization, and seamless integration with your existing Lovable application while ensuring the solution remains scalable and maintainable. I specialize in Node.js, Python, Supabase, PostgreSQL, REST APIs, web scraping, third party API integrations, backend automation, cloud functions, scalable backend architecture, and secure data processing. My focus will be on building a reliable and efficient backend service that integrates smoothly with your existing application and delivers fast, accurate results. I would be happy to discuss your requirements and help build a secure, scalable, and seamless backend solution that integrates perfectly with your existing Lovable real estate platform. Best regards, Nikita Gupta

@umairdev101

I have extensive experience building custom features for real estate webapps and integrating complex data logic into low code platforms like Lovable. I can help you expand the functionality of your Custom Feature for Real Estate Webapp by developing robust backend APIs and implementing precise data extraction tools to populate your property listings. My expertise in JavaScript and database architecture ensures that any new feature will integrate seamlessly with your existing Lovable frontend without disrupting the current user experience. I have previously built scrapers and custom data pipelines for real estate platforms that required high accuracy and real time updates. I am ready to start immediately and can deliver a clean, scalable solution within your budget.

@krupnovdenis

Hello! We can build the backend logic and API endpoint for this feature. 1. Do you already have access to the data source for unit matching and owner lookup? 2. Should we connect this as a Supabase Edge Function or a separate backend service? — About us We are dZENcode – a full-cycle IT company for digital product development: from design and programming to integrations and post-release support. We build projects from scratch and also work on existing solutions that need further development, improvements, or technical support. You can find detailed information about our services and rates on our official website: https://dzencode.com. Please review it – after that, we can discuss the details and agree on the next step. ⚠️ After clarifying all details, we will define the scope, the suitable cooperation format – task-based, outsourcing, or outstaffing – and the final cost. Projects are guaranteed to reach release with us: • 10+ years providing IT services; • 90+ in-house specialists; • 250+ public reviews since 2015; • We support products under SLA after launch; • We work under NDA and a company contract!

@denisSolution

Hi, I'd handle this using a headless browser with selective DOM extraction, paired with a background job queue to avoid blocking frontend requests. The biggest improvement will come from caching matched listings locally to reduce repeated API calls to third-party sources. Once I worked on a property lookup tool where scraping portal pages at scale triggered rate limiting, but limiting extraction to critical nodes and adding short delays kept it stable after a few iterations. I'll wrap the scraping logic in isolated functions and add error handling to ensure partial failures don't affect existing matches. You'll get test coverage before deployment, and I'll document the endpoint so integration with Lovable is straightforward. Support for adjustments is included after delivery. The tool will give visitors instant access to verified owner details, improving trust and lead quality without manual research. It also keeps your platform compliant by relying on public transaction records rather than scraping private data. If we're aligned, I'd be happy to review the current setup and suggest the cleanest path forward. Thanks, Denis.

@irfanui

Hi, I reviewed your project: Custom Feature for Real Estate Webapp. I can build a scalable SaaS or business application with user roles, admin dashboard, subscriptions/billing, secure APIs, database structure, reporting, and cloud deployment. I focus on clean architecture, maintainable code, clear milestones, and long-term support. Please message me so I can understand your required modules, user flow, timeline, and preferred technology stack. Portfolio: https://www.freelancer.com/u/irfanui Regards, Mohammad 4th Dimension Partners

@AnhTVc

hello, I recently built **RealEstate Data Hub** using **Node.js, TypeScript, Supabase, PostgreSQL, Playwright, and REST APIs**. The project involved extracting structured property data from multiple real estate sources, normalizing records, matching them against external property datasets, and exposing secure API endpoints for a web application. For your project, I can build a scalable backend that extracts listing details from supported property URLs, normalizes the data, and matches it against authorized property datasets through secure API integrations. I'll expose the functionality through a clean REST API or Supabase Edge Function that connects seamlessly with your Lovable frontend. To improve reliability, I'll implement robust error handling, caching, rate limiting, and anti-bot resilient scraping techniques where permitted by the source's terms of service. The architecture will be modular, making it easy to extend with additional data providers in the future. Thanks, Tran Viet

@farhan2quasimi

Hi, Having reviewed your technical attachments, this is not a simple scraper — it's a property intelligence pipeline that needs to fit cleanly into your React 19 + Supabase + Cloudflare Workers architecture. My approach: keep scraping in a dedicated external service (Bayut/Property Finder first, modular for more portals), and connect it to your Lovable app via a clean Supabase Edge Function. This protects your main app from scraping instability entirely. The harder part is the matching logic — permit cross-referencing, duplicate detection, exposure history, DLD benchmarking. That needs to be built carefully, not guessed. Suggested phases: Week 1: Architecture + portal feasibility Week 2: Extraction service (Bayut/Property Finder) Week 3: Normalization + permit matching layer Week 4: Supabase integration + hardening Fair price: $900–$1,500 for Phase 1 (extraction + API + basic matching). The listed budget is below the real technical scope — I'd suggest starting with a paid discovery milestone. Ready to jump on a call and validate the approach before committing to full scope. Farhan Technical PM & IT Strategist

@mayankinnovative

Drawing from my extensive 20+ year experience in PHP-based development, your project aligns perfectly with my core expertise. With your Lovable webapp, I understand the need to not only build scalable and maintainable custom features but also enhance its performance and reliability to drive tangible sales results. I've acquired a deep understanding of back-end development, APIs, third-party integrations, and importantly, web scraping - all of which are requisite for your unique property feature. My proficiencies extend beyond mere quick-fixing; I offer long-term support and solutions that stand the test of time. Turning now to the scraping challenge you pose, rest assured I remain well-versed in navigating as well as bypassing any roadblocks thrown by websites like Bayut or Property Finder. My familiarity with JavaScript and mobile app development will further bolster the smooth integration of the scraped data into your frontend. Moreover, it's not just about technicalities: I share your vision of a detailed property search tool that streamlines unit identification, providing accurate owner details. I'm thrilled about the possibility of employing my skills for a definitive improvement on your project. Let's discuss the project further and find out how we can effectively put together our respective strengths to achieve your goals.