— The Problem
Where real estate technology fails
Real estate businesses range from boutique agencies to national portals — but the technology challenges are consistent. Search that can't handle scale. CRM that wasn't built for property pipelines. Data that sits in spreadsheets instead of driving decisions.
Search too slow for portal scale
Generic database queries can't handle millions of property records with complex filters —
bedrooms, price range, radius, polygon draw, school zones. Users leave portals where search takes more than a
second. Elasticsearch is the architecture that solves this.
Disconnected data sources
Property listings, valuation data, sales history, ownership records, and agent CRM sit in
separate systems with no unified view. Agents work around the gaps. Decision-making suffers.
Pipeline management in spreadsheets
Agency deal pipelines tracked in Excel. No visibility on stages, follow-up dates, or agent
performance. Deals fall through the cracks because there's no system enforcing the process.
Manual valuation and appraisal
Comparable analysis done manually — agents pulling recent sales from portals, calculating
adjustments, writing up reports. AI can do the comparable analysis in seconds and present a defensible range.
Document-heavy transaction process
Contracts, disclosure statements, and settlement documents prepared and tracked manually.
High-volume agencies waste significant time on document preparation that should be automated.
No portfolio-level intelligence
Property investors and developers managing multiple assets have no single view of portfolio
performance — rental yield, occupancy, maintenance cost, and capital growth tracked separately per asset.
— What We Build
Real estate technology built for scale and speed
High-Scale Property Search Platforms
Elasticsearch-powered search across millions of properties with sub-second response.
Geo-spatial filters, radius search, map-draw polygon, and complex multi-field queries. We built
EnrichedRealEstate — 42 million US properties, 0.4s average search response.
Agency CRM & Pipeline Management
Zoho CRM configured for real estate — lead capture, property matching, viewing
schedules, offer tracking, and settlement workflow. Every deal stage tracked, every follow-up automated, no
leads falling through gaps.
AI Valuation & Comparable Analysis
ML models on your transaction history and market data. Enter a property address and get
a comparable sales analysis, valuation range, and confidence score in seconds — replacing the manual comp
pull that takes an agent an hour.
Portfolio & Investment BI
Unified dashboard for property investors and developers — rental yield, occupancy rate,
maintenance cost, capital growth, and portfolio ROI in one view. Identify underperforming assets and model
disposal scenarios.
Property Data Aggregation & Enrichment
Ingest and normalise property data from multiple sources — council records, valuation
databases, ownership registries, market feeds — into a single clean dataset ready for search, analytics, or
AI training.
Transaction Document Automation
Standard contracts, disclosure statements, and letters generated from CRM data
automatically. For high-volume agencies, this eliminates hours of document preparation per week without
compromising accuracy.
We built EnrichedRealEstate — 42 million US properties at sub-second search
The US property intelligence platform built by Infomaze ingests and normalises data across
42 million property records. Agents and investors search by address, radius, polygon, school zone, ownership
type, and 40+ additional filters — with sub-second response on any query. Elasticsearch was the architecture
choice that made this possible. Generic SQL databases couldn't handle it.
42M
Properties indexed
<1s
Search response
40+
Filter dimensions
Geo
Spatial search
— Featured Case Study
42 million properties. Sub-second search. Built for scale from day one.
Real Estate · Search Platform
EnrichedRealEstate — US Property Intelligence Platform, 42M Records
42M
Properties indexed
<1s
Search response time
40+
Search filter dimensions
Built on Elasticsearch with geo-spatial search across 42 million US property records.
Normalised data pipeline aggregating ownership, valuation, and transaction history. Sub-second search on radius,
polygon, school zone, and 40+ property attributes. Replaced a 2+ minute SQL query approach.
Elasticsearch · Laravel · Python · ETL PipelineRead full case study →
— Integrations
Connects with the real estate data stack
Elasticsearch
High-scale property search with geo-spatial capability
Zoho CRM
Agency pipeline and lead management
Google Maps API
Map display, draw search, and location enrichment
Power BI
Portfolio and market intelligence dashboards
Land / Title APIs
Ownership and title registry data ingestion
Valuation Feeds
CoreLogic, Zillow, domain data integration
Zoho Campaigns
Automated property alerts and nurture sequences
Document Automation
Contracts and disclosures from CRM data