Predictive analytics
Amazon SageMaker models forecast property prices and market trends with over 92% reported accuracy.
Available on AWS Marketplace 
EstateEdge
AI-powered real-estate analytics: priced, positioned, predicted.
Phoenix EstateEdge is an AI-powered real-estate analytics platform built on AWS. It transforms raw CRM and market data into actionable business insights, combining competitor pricing, demand trends and internal sales performance into a unified dashboard, with SageMaker predictive models forecasting price and market movement.
What it does
Feature set
Unified dashboard
CRM data, competitor analysis, market pricing, demand trends and business analytics, all in one place.
Real-time visualization
Amazon QuickSight delivers real-time dashboards with customisable reporting for KPI monitoring and executive review.
Enterprise-grade delivery
Deployed and supported by Phoenix, from AWS integration through configuration and ongoing tuning.
Use cases
Where it shows up
- Evaluating live market prices for a development portfolio
- Predicting demand and price movement across submarkets
- Monitoring sales-team performance against competitor listings
- Improving conversion rate through data-driven pricing
- Identifying investment opportunities in adjacent segments
Built on: AWS · Amazon SageMaker · Amazon QuickSight · CRM data integration
FAQ
Frequently asked
What data does EstateEdge need to run?
A blend of external market data (live listings, competitor pricing, macro indicators) and your own CRM, sales and inventory data. The AWS-native ingestion layer handles both: external via ongoing scraping and API feeds, internal via secure connectors into your CRM.
Is EstateEdge SaaS or deployed on our AWS account?
Deployed as a tuned instance per customer inside their AWS account via AWS Marketplace. Same core engine, customer-specific data ingestion, KPIs and dashboards. Your data never leaves your boundary.
How accurate are the price and demand forecasts?
Amazon SageMaker models are benchmarked per customer against the target KPI (pricing win-rate, listing velocity, gross margin). Reported accuracy over 92% on price forecasting for customers with reasonable historical depth; margin improvements track over successive quarters as the model learns local dynamics.
Which markets or regions are supported?
Live coverage across MEA real-estate markets. New markets are on-boarded per customer engagement: the ingestion layer is region-agnostic; the tuning work is in per-market feature engineering and normalisation.
How is pricing structured on AWS Marketplace?
Subscription-based against contracted portfolio size and analyst-user counts. Billing flows through your AWS account. Enterprise commitments and multi-year terms are available; contact us for pricing tiers.
The earliest conversations are usually the most useful.
Whether you are pricing a development portfolio or building demand forecasts across submarkets, start with a conversation.
