Whiteboard — ML-Powered Real Estate Operations Platform

A business operations platform built for a real estate transaction coordination company. Beyond standard transaction tracking and billing, the standout feature is a suite of 20+ ML-powered signal detectors that surface actionable business intelligence in real time.

Why the ML Layer Matters

Transaction coordination companies track dozens of agents, each with their own submission patterns, revenue contributions, and performance trends. Manual monitoring doesn’t scale. The signal detection system establishes per-agent baselines using historical data, then flags deviations automatically.

Signal Detectors

• Hot/cold streak detection — identifies agents whose performance is trending significantly up or down relative to their personal baseline
• Cadence anomaly detection — flags when an agent’s contract submission frequency deviates from their established pattern (early warning for churn or capacity issues)
• Revenue forecasting — projects future revenue based on current pipeline and historical close rates
• Concentration risk analysis — alerts when too much revenue depends on a single agent or client
• Year-over-year comparisons — contextualizes current performance against seasonal patterns

All 20+ detectors are built with php-ml, establishing individual agent baselines rather than comparing against company averages — because an agent who normally submits 3 contracts/month dropping to 1 is a very different signal than a high-volume agent dropping from 30 to 28.

Architecture

Symfony 7 backend with Doctrine ORM and FOSRestBundle, React 18 + TanStack Query frontend (with some legacy Vue 2 still in place — a real-world codebase, not a greenfield rewrite). Pushover integration for real-time alert notifications when signals fire.