DomuSearch — A Case Study

TL;DR

We built DomuSearch, an interactive real-time property analytics platform for a progressive realtor in Denmark. Using React, Node.js, MySQL, Redis, and trusted government APIs (DAWA and EMOWeb), the platform delivers accurate building data, energy labels, CO₂ reduction insights, and automated change notifications — helping buyers and investors make smarter property decisions instantly. The result: high-quality data-driven proposals, a measurable environmental impact, and a nomination for "This Year's Sustainability Prize" by the Danish Real Estate Industry Association.

Problem Overview

In today's fast-growing real estate market, accurate data and real-time insights aren't a bonus — they're a necessity. Realtors in Denmark were relying on outdated reports with no way to detect property changes or communicate them to buyers in time. There was no tool that combined live building data, energy performance, and CO₂ insights in one place — leaving investors unable to identify errors, inefficiencies, or improvement opportunities across their portfolios.

• Outdated property reports caused inaccurate analysis and poor investment decisions
• No real-time notification system when property data or energy labels changed
• APIs handling large volumes of building data were too slow for practical use
• Issues were flagged to clients with no accompanying solutions — unhelpful and incomplete
• No visibility into energy labels or CO₂ reduction potential across property portfolios

Role & Responsibilities

• Role: Full-stack development team
• Responsibilities:
  • Design and build the full property analytics platform end-to-end
  • Integrate government APIs — DAWA and EMOWeb — for reliable, real-time building data
  • Build a queue-based background processing system for fast API responses under heavy data loads
  • Develop automated change detection and user notification system
  • Implement OAuth and token-based API security
  • Deliver energy label analysis and CO₂ reduction reporting features
  • Integrate Slack, Mandrill, S3, and Rollbar for communications, storage, and monitoring

Project Context

• Client: Progressive real estate realtor based in Copenhagen, Denmark
• Industry: Real estate — property analytics and sustainability
• Purpose: Give realtors and property investors an intelligent, data-driven platform to engage buyers and improve decision-making
• Constraints: Large volumes of building data requiring fast responses, dependency on live government APIs, strict data accuracy requirements, and the need to surface actionable solutions — not just raw issues

My Approach

We started by mapping exactly what realtors and buyers needed from property data — not just raw numbers, but insights they could act on immediately. The architecture was designed around two priorities: speed for the user and accuracy from the source. Background processing was introduced early so API response times stayed fast regardless of data volume.

• Discovery: Identified the full lifecycle of a property query — from search to report delivery to change notification
• API Strategy: Evaluated and integrated government-grade DAWA and EMOWeb APIs to guarantee data accuracy and eliminate outdated report dependency
• Queue Architecture: Designed background processing so users receive instant acknowledgement while heavy data logic runs behind the scenes
• Solution-first Thinking: Built the platform to not just flag property issues but pair each one with a recommended action

Research & Insights

Key Findings from Discovery

• Realtors needed live data — not static reports — to confidently engage buyers with up-to-date information
• Property investors wanted to detect errors and improvement opportunities across their portfolios, not just view data
• End users expected notification when anything changed — energy labels, building data, or compliance status
• Surfacing a problem without a solution frustrated users; actionable recommendations were essential
• Performance was critical — a slow platform with accurate data was as unusable as a fast one with wrong data

Competitive Research

• Existing real estate tools in Denmark relied on static reports with no real-time government data integration
• Energy label and CO₂ data were siloed — no platform brought them together with property search and analytics
• No competitor offered automated change detection and proactive user notifications

User Persona

• Name: Simon
• Role: Real estate professional, Copenhagen
• Goals: Engage buyers with accurate real-time data, identify energy improvement opportunities, stay ahead of property changes automatically
• Pain Points: Outdated reports, no change alerts, slow data retrieval, no actionable insights on energy performance

Information Architecture

• Property Search — search and retrieve real-time building data via DAWA and EMOWeb APIs
• Analytics Dashboard — energy labels, CO₂ reduction potential, and portfolio-level insights
• Report Generation — background queue processes large data volumes and notifies users when ready
• Change Detection — monitors live government data for updates and alerts realtors automatically
• Issue and Solution View — surfaces property problems alongside recommended corrective actions
• Notification Panel — centralised in-app notifications generated on every automatic update or significant system action, so users always know what changed and why
• Background Job Monitor — real-time visibility into running and recently completed background tasks per account, giving users clarity on async processes happening behind the scenes
• Notification Layer — Slack and Mandrill integrations for real-time and email-based alerts

Visual Language

The interface was built to make dense property and energy data feel approachable and actionable. Clear data hierarchies, visual energy label indicators, and summary cards kept the experience clean despite the complexity underneath. The UI was designed for realtors — not data analysts — so everything surfaces the "so what" before the raw numbers.

Wireframes & Early Ideas

Early wireframes centred on the property search and report view — the two moments where users spent most of their time. A key decision was to surface CO₂ reduction and energy label data alongside standard building information rather than burying it in a separate tab. The queue notification pattern was introduced in wireframing to set the right expectation: request a report, get notified when ready, no waiting at a loading screen.

Designing Solutions

Problem: Outdated property data causing inaccurate reports and poor buyer decisions

• Integrated DAWA APIs and EMOWeb — trusted Danish government sources — as the sole data layer, eliminating outdated reports entirely
• Data is fetched live on every query, ensuring realtors always present buyers with current, accurate information

Problem: APIs too slow when handling large volumes of building data

• Introduced a queue-based background processing system — API requests return instantly while heavy business logic runs behind the scenes
• Users are notified via Slack or email (Mandrill) once their report is ready — no waiting at a loading screen
• Redis used for fast caching and queue management, keeping the system responsive under load

Problem: Realtors not informed when property data or energy labels changed

• Built a background change detection engine that continuously monitors live government data for updates
• When changes are detected, realtors are automatically notified so they can communicate updates to end users immediately

Problem: Issues surfaced to clients with no solutions — unhelpful and incomplete

• Every flagged property issue is paired with a recommended corrective action within the platform
• CO₂ reduction opportunities and energy efficiency improvements are presented as actionable proposals, not raw data
• Realtors can use these insights directly in investment and sustainability discussions with clients

Tech & Implementation

• Frontend: React with JavaScript — clean, responsive UI designed for data-heavy workflows
• Backend: Node.js with Express — fast and reliable for API-heavy, real-time data applications
• Database: MySQL for structured property data; Redis for caching and queue management
• API Integrations: DAWA APIs and EMOWeb for live government building data; Slack for real-time notifications; Mandrill for email delivery; S3 for report storage; Rollbar for error monitoring
• Security: OAuth with token-based API authentication strategy throughout
• Deployment: Release cycle deployment process — breaking changes managed under strict version control

Real-world Features & Highlights

• Live government data integration → DAWA and EMOWeb APIs eliminate outdated reports entirely
• Queue-based report generation → instant response to users, background processing, notification on ready
• Automated change detection → realtors notified automatically when property or energy data updates
• Energy label analytics → clear visual overview of energy performance across a property portfolio
• CO₂ reduction insights → actionable proposals for energy efficiency improvements per property
• Issue + solution pairing → every flagged problem comes with a recommended corrective action
• Portfolio error detection → investors can identify inaccuracies and improvement opportunities at scale

Results & Impact

• Delivered high-quality building data to support accurate analysis and investment decision-making across property portfolios
• Developed data-driven proposals for strategic investment and energy efficiency improvements used directly by realtors in client conversations
• Created a clear, actionable overview of energy labels and CO₂ reduction potential — making sustainability measurable for the first time for this client
• Enabled property investors to analyse portfolios, detect errors, and identify improvement opportunities at scale
• Nominated for "This Year's Sustainability Prize" by the Danish Real Estate Industry Association — recognising the platform's significant contribution to sustainable development

Challenges & Learnings

• Data accuracy at speed — government APIs are authoritative but not optimised for high-frequency queries; the queue system was the critical architectural decision that solved both together
• Volume without friction — handling large building data volumes while keeping the UI fast required a disciplined separation between what the user sees and what runs in the background
• Actionable insights, not just data — early feedback showed raw issue lists frustrated users; pairing every issue with a recommended action significantly improved adoption
• Change detection reliability — monitoring live government data required careful diffing logic to avoid false positives and unnecessary notifications
• Sustainability as a product feature — framing CO₂ and energy data as investor tools rather than compliance outputs was a key decision that contributed directly to the sustainability prize nomination

Takeaways

• Real-time data changes everything: Replacing static reports with live government API integration fundamentally changed how realtors could engage buyers — accuracy became a competitive advantage
• Background processing is a UX decision: Moving heavy logic to a queue wasn't just a technical choice — it directly shaped how users experienced the platform and removed the single biggest friction point
• Solutions beat problem lists: Pairing every flagged issue with a recommended action transformed the platform from a diagnostic tool into a decision-making tool
• Sustainability data has business value: Integrating energy labels and CO₂ insights created a new category of data-driven proposal that realtors could use to win investment mandates
• Domain depth drives recognition: Deep understanding of Danish real estate data standards and government APIs was what made the sustainability prize nomination possible

Next Steps

• Expand CO₂ modelling to support full portfolio-level sustainability reporting
• Add predictive energy label scoring based on planned renovation data
• Mobile application for on-the-go property insights and change alerts
• Deeper integration with investment platforms for direct data-driven proposal generation
• Expand to additional Scandinavian markets with localised government API support

Client Feedback

"DomuSearch has been nominated for this award. It's great that your work is making such a meaningful impact on the Danish real estate industry."

— Simon, Real Estate Professional, Copenhagen

DomuSearch was nominated for "This Year's Sustainability Prize" by the Danish Real Estate Industry Association, recognising the platform's significant contribution to sustainable development and its role in bringing visibility and structure to energy-labelled property data across the Danish real estate sector.

Call to Action

If you're looking to build a data-driven analytics platform or integrate real-time government data into your product, contact us at WhizCloud — we'd love to partner with you.