AI Real Estate Listings Site
Budget: $750 – $1,500 USD
I need a property-listings website built from the ground up, and I’d like it created by someone who actively uses AI tools to speed up clean, scalable development.
Core scope
The site’s primary role is to publish residential and commercial listings that visitors can filter quickly. Advanced search filters (price range, bedrooms, location, etc.) and an interactive map must work together so users can see matching properties plotted in real time.
User experience
• Visitors create an account or sign in with Google/Apple.
• Registered users can save searches, bookmark favourite listings, leave star-rated reviews on properties or agents, and submit inquiry forms that arrive straight to my CRM/email.
• Inquiry forms trigger an automatic confirmation email to the prospect and a notification to me.
Back-office essentials
Admins (my team) add, edit, or bulk-import listings via a secure dashboard. Data fields include photos, videos, amenities, floor-plans and geolocation coordinates that power the map view. I’d like routine tasks—image optimisation, meta-tag generation, duplicate detection—automated with the AI solutions you already rely on.
Stack & integrations
Feel free to propose the stack you’re most productive in—React, Next.js, Laravel, Django, or a no-code platform enhanced with custom code—so long as the final product is responsive, SEO-friendly, and easily portable to mainstream hosting. Leaflet, Mapbox or Google Maps are all acceptable for the map layer. Stripe or PayPal hooks can be left stubbed for future paid upgrades.
Deliverables
1. Fully functional, responsive website running on a staging URL
2. Admin dashboard with listing CRUD, user management and analytics snapshot
3. Front-end: advanced filters, interactive map, registration/login, reviews, inquiry workflow
4. Written hand-over: stack overview, deployment steps, AI automations used, API keys list (placeholders only)
5. Two weeks of light post-launch support to squash any launch bugs
Acceptance criteria
• PageSpeed score ≥ 90 on mobile
• Filters return results < 1 s on 10k listings dataset
• Map pins match listing coordinates exactly (tested on sample CSV)
• All forms send email notifications successfully
If you already combine code with AI co-pilots and can deliver the above, I’m ready to get started right away.
Core scope
The site’s primary role is to publish residential and commercial listings that visitors can filter quickly. Advanced search filters (price range, bedrooms, location, etc.) and an interactive map must work together so users can see matching properties plotted in real time.
User experience
• Visitors create an account or sign in with Google/Apple.
• Registered users can save searches, bookmark favourite listings, leave star-rated reviews on properties or agents, and submit inquiry forms that arrive straight to my CRM/email.
• Inquiry forms trigger an automatic confirmation email to the prospect and a notification to me.
Back-office essentials
Admins (my team) add, edit, or bulk-import listings via a secure dashboard. Data fields include photos, videos, amenities, floor-plans and geolocation coordinates that power the map view. I’d like routine tasks—image optimisation, meta-tag generation, duplicate detection—automated with the AI solutions you already rely on.
Stack & integrations
Feel free to propose the stack you’re most productive in—React, Next.js, Laravel, Django, or a no-code platform enhanced with custom code—so long as the final product is responsive, SEO-friendly, and easily portable to mainstream hosting. Leaflet, Mapbox or Google Maps are all acceptable for the map layer. Stripe or PayPal hooks can be left stubbed for future paid upgrades.
Deliverables
1. Fully functional, responsive website running on a staging URL
2. Admin dashboard with listing CRUD, user management and analytics snapshot
3. Front-end: advanced filters, interactive map, registration/login, reviews, inquiry workflow
4. Written hand-over: stack overview, deployment steps, AI automations used, API keys list (placeholders only)
5. Two weeks of light post-launch support to squash any launch bugs
Acceptance criteria
• PageSpeed score ≥ 90 on mobile
• Filters return results < 1 s on 10k listings dataset
• Map pins match listing coordinates exactly (tested on sample CSV)
• All forms send email notifications successfully
If you already combine code with AI co-pilots and can deliver the above, I’m ready to get started right away.
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