CMA Engine
Automated comparative market analysis at portfolio scale
CMA Engine normalizes listing, sale and assessor data, selects comparables with explainable scoring, and produces adjustment grids that an appraiser or agent can defend line by line.
- Real Estate Technology
- Business Intelligence
- Workflow Automation
Business problems solved
What was broken
Comp selection is subjective
Two agents produce two different values from the same data set.
Reports take hours
Manual grid building and formatting consume the highest-value hours of the week.
No audit trail
Adjustments are rarely documented in a way that survives scrutiny.
Primary features
What we built
Explainable comp scoring
Each comparable shows why it scored, across distance, recency and feature deltas.
Adjustment grid
Editable grid with automatic reconciliation and variance flags.
Report studio
Branded, client-ready reports generated in seconds.
Portfolio mode
Batch valuation across hundreds of subject properties.
Interactive demonstration
Explore CMA Engine
Switch modules, step through the workflow and query the assistant. Everything runs on mock data inside this guided experience.
CMAs generated
4,610
+27%
Avg build time
48 sec
-96%
Value variance
±2.1%
-1.4pt
Active markets
34
+6
Operational trend
CMAs generated · Portfolio valuations
Technology stack
What it runs on
- React
- TypeScript
- PostgreSQL
- Supabase
- REST APIs
- Business Intelligence
- Role Based Security
- Analytics
Development highlights
Engineering notes
- Explainable scoring model with per-factor contribution display
- Market regression pipeline refreshed nightly
- Report engine with brand theming per brokerage
Future roadmap
Where it goes next
- Automated appraisal review mode
- MLS partner integrations
- Forecast-adjusted valuations
Architecture
System layers
- 01
Analyst Console
- 02
API Layer
- 03
Authentication
- 04
Valuation Engine
- 05
PostgreSQL
- 06
Report Storage
- 07
Analytics
Estimated demonstration metrics
Scope of the build
Illustrative scale for this guided experience.
0
Estimated screens
0
Estimated features
0
Estimated API endpoints
0
Estimated database tables
High
Architecture complexity
5 months
Development timeline
Performance target
Batch of 500 valuations in under 4 minutes
Estimated Demonstration Metrics — illustrative values for this guided experience, not measured production statistics.
Workflow walkthrough
How work moves through it
- 1
Define subject
Subject property attributes normalized against assessor records.
- 2
Select comps
Scored candidate set with transparent weighting.
- 3
Adjust
Feature deltas priced from market regression coefficients.
- 4
Reconcile
Weighted value range with variance flags.
- 5
Deliver
Branded report exported and tracked.
Product walkthrough
Recorded tour
Video placeholder
Guided CMA Engine walkthrough
Core capabilities
- Comparable scoring
- Adjustment grids
- Batch valuation
- Client reporting
Continue the tour
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