LeaseTrack Specification

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LeaseTrack

Rental Trends. Ownership Patterns. Compliance Checks.

An open source AI platform that analyzes U.S. rental markets to identify affordability gaps, ownership patterns, landlord compliance issues, and market anomalies through AI driven analytics and public data integration.

Mission

LeaseTrack brings transparency to the U.S. rental housing market by combining rental listings, public records, ownership information, licensing databases, and artificial intelligence into a single open platform. The system helps researchers, policymakers, tenant advocates, investors, journalists, and consumers better understand rental markets through objective data analysis rather than isolated listings.

Core Objectives

Analyze rental affordability by ZIP Code.
Compare rents against qualifying income standards.
Detect unusual rental market activity.
Monitor ownership concentration.
Verify landlord licensing compliance.
Provide explainable AI generated findings.
Produce interactive visualizations.
Support community driven improvements.

Feature Modules

Rental Market Module

Rental Collection

Collect rental listings from:

MLS rental listings
Zillow Rentals
Apartments.com
Rent.com
Realtor rental listings
Facebook Marketplace
Craigslist
Nextdoor
Additional public rental websites

Unit Classification

Support:

Studio
Efficiency
One Bedroom
Two Bedroom
Three Bedroom
Four Bedroom
Five Plus Bedrooms
Single Family Rentals
Condominiums
Townhomes
Duplexes
Multifamily Units
Accessory Dwelling Units

Affordability Module

Compare:

Average rent
Median rent
Median household income
Standard qualifying income
Required annual income
Required monthly income

Calculate:

Rent to income ratio
Required qualifying salary
Local affordability score
Market affordability index

Identify:

Underpriced markets
Overpriced markets
Affordable housing shortages
High burden rental markets

AI Analysis Module

Automatically analyze flagged markets.

Evaluate:

Rapid rent increases
Historical rent trends
Rental inventory changes
Vacancy trends
Pricing anomalies
Seasonal patterns
Neighborhood trends
Housing shortages

Generate:

AI summaries
Market explanations
Risk assessments
Affordability reports
Trend reports

Ownership Intelligence Module

Determine ownership type.

Identify:

Individual owners
Corporate owners
LLC ownership
Trust ownership
Institutional investors
Government ownership
Nonprofit ownership

Analyze:

Ownership concentration
Absentee ownership
Corporate acquisition patterns
Portfolio size
Geographic ownership clusters

Licensing Compliance Module

Review licensing requirements where available.

Verify:

Rental licenses
Landlord registrations
Business licenses
Inspection requirements
Registration renewals

Flag:

Missing licenses
Expired licenses
Missing registrations
Potential compliance issues

Public Records Module

Analyze:

Property records
Deeds
Tax assessments
Ownership transfers
Tax liens
Code violations
Permit history
Eviction filings where publicly available
Foreclosure records
Parcel information

Market Monitoring Module

Track:

New rental listings
Removed listings
Price reductions
Price increases
Time on market
Listing history
Rental inventory
Market velocity

Broker Analytics Module

Review MLS activity.

Analyze:

Listing broker activity
Listing agent activity
Repeated market participation
Rental concentration
Geographic specialization

Geographic Analysis Module

Support:

National analysis
State analysis
County analysis
Municipality analysis
ZIP Code analysis
Neighborhood analysis
Census tract analysis

Interactive mapping includes:

Heat maps
Ownership maps
Affordability maps
Compliance maps
Market activity maps

Historical Analytics Module

Maintain historical datasets for:

Rent history
Ownership changes
Licensing history
Inventory history
Market trend history
Affordability history

Generate:

Trend comparisons
Historical reports
Growth analysis

Reporting Module

Generate:

ZIP Code reports
City reports
County reports
State reports
Ownership reports
Compliance reports
AI summaries
Affordability reports
Market trend reports

Export:

PDF
CSV
JSON
Excel

Notification Module

Notify users of:

New affordability issues
Large rent increases
Ownership changes
Licensing issues
New market anomalies
Significant market trends

Support:

Scheduled reports
Weekly updates
Monthly summaries
Custom alerts

Dashboard Module

Interactive dashboard includes:

Market overview
Rental trends
Affordability charts
Ownership charts
Compliance status
Heat maps
Historical graphs
AI generated insights

Community Module

Support:

Community contributions
Public issue reporting
Data validation
Research collaboration
Documentation improvements

API Module

Provide APIs for:

Rental statistics
Affordability calculations
Ownership lookups
Licensing verification
Market reports
Historical trends
AI summaries

Artificial Intelligence Features

The AI system can:

Explain affordability gaps
Detect market anomalies
Identify ownership trends
Analyze rental behavior
Produce plain language reports
Forecast rental trends
Recommend additional investigation
Compare neighboring markets
Detect unusual ownership concentration
Identify emerging housing issues

Technology Stack

Backend

Python
FastAPI
Celery
Redis

Database

PostgreSQL
PostGIS

Data Processing

Pandas
NumPy
Scikit Learn
TensorFlow

Artificial Intelligence

Large Language Models
LangChain
Vector Database support
Retrieval Augmented Generation
Explainable AI

Frontend

React
Tailwind CSS

Mapping

Leaflet
Mapbox

Visualization

Plotly
D3.js

Web Collection

BeautifulSoup
Playwright
Selenium

Design Principles

Modular architecture
Open source
Explainable AI
Transparent calculations
Privacy conscious
Public data first
Extensible plugin architecture
API first design
Local deployment support
Scalable infrastructure

Intended Users

Researchers
Housing advocates
Journalists
Investors
Property managers
Government agencies
Universities
Nonprofit organizations
Community planners
Consumers

Future Modules

Fair Housing Analysis
Rent Control Analytics
Housing Supply Modeling
Gentrification Indicators
Economic Mobility Analysis
Rental Fraud Detection
Corporate Portfolio Intelligence
Tenant Displacement Indicators
Housing Policy Simulation
Infrastructure Impact Analysis
School District Correlation
Transit Accessibility Analysis
Environmental Risk Mapping
Disaster Recovery Monitoring
Predictive Market Forecasting

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
Required attribution:
- Roxanne Ardary
- roxanneardary.com

Optional

Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- https://roxanneardary.com/leasetrack/

License & Notice Requirements

LeaseTrack is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

By contributing to this project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to: Roxanne Ardary and roxanneardary.com.
LeaseTrack specificiations are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments. Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – LeaseTrack

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions to this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – March 29, 2026
Created the repository for LeaseTrack. Designed and defined the AI powered rental market analysis platform, including affordability analysis, ownership tracking, and compliance monitoring.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – LeaseTrack

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points:

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.