Property Portfolio Analytics

The Challenge

Real estate firms managing large portfolios struggle to consolidate data across properties, accurately value assets, and identify underperforming investments before they erode returns.

Root Cause Analysis

Fragmented data: Property management, leasing, financial, and market data spread across disconnected systems
Lagging valuations: Manual appraisals are slow, expensive, and often outdated by the time they're completed
Reactive management: Occupancy issues and tenant churn are detected too late to course-correct
Limited benchmarking: Difficulty comparing performance across properties, markets, and asset classes

How We Solve This with Cloud Technologies

Unified Portfolio Intelligence Platform

We build cloud-native analytics platforms that consolidate all property data into a single source of truth:

Automated valuation models (AVMs): ML-driven property valuations updated in real-time using market comps, rental income, and macro indicators
Occupancy forecasting: Predict vacancy rates 6-12 months ahead using tenant behavior signals and market trends
Investment scoring: AI models rank acquisition targets and disposition candidates based on risk-adjusted returns
Benchmarking dashboards: Compare NOI, cap rates, and occupancy across the entire portfolio

Reference Architecture

Data ingestion: APIs and ETL pipelines from Yardi, MRI, CoStar, and public records
Data lake: Delta Lake with medallion architecture for property, financial, and market data
ML platform: Databricks ML for valuation models and forecasting
Visualization: Power BI dashboards with drill-down from portfolio to individual unit level
Alerts: Automated notifications for lease expirations, maintenance thresholds, and market shifts

Business Impact

20% faster investment decisions with real-time portfolio analytics
Improved NOI by 8-12% through proactive occupancy management
Accurate valuations within 3% of appraised value using AVM models