A National Real-Estate Platform, Launched Fast with Vibe Coding
Designing,ย building and SEO-engineering rele.one across all of Australia โ on Next.js and Python.
Client Overview
Rele partnered withย Prakash Software Solutions (PSSPL)ย to design and buildย rele.oneย โ a modern, national real-estate marketplace for Australia, covering property toย buy, rent, and investย across all eight states and territories.
Entering a category dominated by long-established incumbents, Rele needed a polished, feature-complete platform โ with AI-powered search, verified agents, and live market data โ that was also fast and highly visible in search from day one. A traditional multi-year build was not an option.ย
PSSPL delivered the platform end to end using aย vibe coding approach: an AI-assisted development workflow that compresses build time while keeping experienced engineers in control of architecture, performance, and SEO.
Industry
Real Estate / PropTech
Function
Web Platform Development
Location
Australia
Project Duration
5 Weeks
Services Provided
- AI-powered real-estate marketplace development
- Vibe coding โ AI-assisted rapid development (Claude Code + Lovable / v0 / Bolt)
- Next.js server-side-rendered web application
- Python backend, data and AI services
- AI natural-language property search
- SEO engineering โ technical SEO, structured data, programmatic location pages
- Agent verification and listings management
- Buyer tools (calculators) and market-data integration
Technologies Used
Frontend
Next.js, React (server-side rendering)
Backend
Python
Vibe Coding (AI-assisted)
Claude Code, Lovable, v0, Bolt
Search & AI
Natural-language AI property search over structured filters
SEO & Discovery
SSR, schema / structured data, programmatic state & suburb pages
Content & Tools
News, blogs, guides, affordability & borrowing-power calculators
The Challenge
Building a nationalย real-estateย marketplace is a large undertaking. In this category, discovery happens on searchย engines, buyers expect a modern search experience, and trust is everything. Rele needed all of it, delivered fast enough to compete with players that have had years and large teams.
Some of the major challenges included:
- Delivering a full platform โ sale, rent, sold, new developments, agents, news,ย guidesย and calculators โ not just a landing page
- Providing both natural-language AI search and traditional filters across every state and territory
- Achieving strong technical SEO so the platform ranks and captures organic traffic from launch
- Verifying agents and listings so users can transact with confidence
- Covering all 8 Australian states and territories with location-specific pages
- Reaching a credible, feature-complete product quickly, under real time-to-market pressure
Project Highlights
โVibe codingย letย us move at a pace a traditional buildย couldnโtย match โ but the discipline never dropped. AI generated first-draft UI and scaffolding; our engineers owned the architecture, the Python services, the performance, and the SEO.ย Thatโsย how you ship something this broad, this fast, without it becoming fragile.โย
Kiran Oza
Project Manager, PSSPL
How PSSPL Helped
PSSPL built rele.one to fit the way modern property search actually works.ย AI app builders (Lovable, v0, Bolt) produced page layouts and components rapidly;ย Claude Codeย drove application logic, Python services, API integrations, and searchย behaviour โ with every change reviewed by engineers rather than accepted blindly.
Because real-estate discovery is search-led, SEO was treated as a core engineering workstream, not an afterthought. Theย Next.jsย foundation was chosen precisely for server-sideย renderingย that gives search engines clean, fast, crawlable pages, backed by structured data and scalable location pages.ย
Outcome:ย ย A live, feature-complete, search-visible marketplace spanning every Australian state โ delivered far faster than a traditional build.ย
Key Platform Capabilities
Feature
Description
AI Property Search
Natural-language search (e.g.ย โ3 bed Sydneyโ, โQLD investโ) alongside classic manual filters
Buy ยท Rent ยท Sold
Unified listings across sale, rental, and sold properties, filterable by state and suburb
Nationwide Coverage
Browse by all 8 states and territories โ NSW, VIC, QLD, SA, WA, TAS, NT, ACT
Verified Agents
Background-checked, locally rated licensed agents with profiles for trusted transactions
Live Market Data
Real-time price trends, auction clearance rates, and suburb reports
Buyer Tools
Affordability calculator, borrowing-power calculator, and dedicated insights
New Developments
A dedicated section for off-the-plan and new-build opportunities
Insights & Content
Property news, RBA rate updates, blogs, and suburb-by-suburb guides for SEOย
For Agents
An agent onboarding and listing pathway to grow supply on the platform
Implementation Journey
PSSPL delivered the platform in four phases, each designed to move fast while keeping quality and SEO strength intact.ย
Discovery & Product Definition
Mapped the product scope, user journeys (buy, rent, invest, agents), and information architecture across all states and suburbs, and defined the SEO and search requirements up front.
Rapid Build via Vibe Coding
Generated layouts, components, and first-draft logic with AI tools (Lovable, v0, Bolt, Claude Code), then refined and hardened them by hand โ building the Next.js frontend and Python services in tight, iterative loops.
SEO Engineering & Integration
Implemented server-side rendering, structured data, clean URL and internal-linking structure, and scalable location pages; integrated AI search, market data, verification, and buyer tools.
Testing, Optimization & Launch
Tested across states and devices, tuned performance and crawlability, and launched a feature-complete national platform.
Key Business Outcomes We Delivered
National platform โ delivered
A comprehensive, production-grade property marketplace live across Australia.
8 states & territories
Full national coverage โ NSW, VIC, QLD, SA, WA, TAS, NT, and ACT.
60% faster to market
AI-assisted vibe coding compressed delivery versus a traditional hand-built approach.
30% lower build cost
Less time on boilerplate meant more budget spent on search quality, data, and polish.
20% organic traffic growth
SEO-first Next.js architecture built to capture location-specific property search demand.
Building Modern Platforms, Faster
This case study shows how PSSPL uses AI-assistedย vibe coding to ship serious, search-visible products quickly โ without cutting corners. AI handled the heavy lifting of UI and scaffolding; PSSPL engineers owned architecture, Python services, performance, and SEO. The result is rele.one: a modern Next.js marketplace spanning every Australian state.
Letโs build web platforms that are fast to market, technically SEO-strong, and engineered to scale.
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