🏭 Building an AI-Powered Industrial Property Analysis System from Scratch

Analyze, Compare, and Discover Properties Across Cook County, Dallas County & Los Angeles County — with Python, Flask, Next.js & Tailwind 🚀

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👋 Introduction

Industrial real estate data is often fragmented, difficult to compare, and not readily available in a unified format. As someone passionate about AI and backend engineering, I decided to build a Property Analysis System that:

• Fetches data from public APIs (or mock sources)

• Cleans and standardizes property data

• Analyzes properties using a custom similarity algorithm

• Displays comparables with confidence scores

All while being API-ready and frontend-powered!

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📌 Key Goals

✅ Automatically discover county APIs
✅ Extract & clean industrial property data
✅ Analyze properties with a weighted similarity model
✅ Expose the system via RESTful APIs
✅ Build a fast, beautiful frontend using Next.js + Tailwind CSS

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🧠 Core Features

🔍 API Discovery Engine

A smart agent that:

• Connects to 3 county APIs (Cook, Dallas, LA)

• Automatically maps field names to a standard schema

• Handles rate limiting & errors gracefully

🏗️ Industrial Property Extractor

• Validates property data

• Filters for industrial zoning (M1, M2, I-1, etc.)

• Converts everything to a clean, standardized format

📊 Comparable Discovery Agent

A scoring engine based on:

This engine returns confidence levels (High/Medium/Low) for each comparable property using a weighted similarity model.

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⚙️ Tech Stack

Backend:

• Python 3.10

• Flask

• Pandas, NumPy, Geopy

• aiohttp for async API calls

Frontend:

• Next.js (React)

• Tailwind CSS

• Axios

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💻 How It Works (Architecture Overview)

            +----------------------+
            |  County APIs (Real)  |
            |  or Mock Data Source |
            +----------+-----------+
                       |
                       v
        +-------------------------------+
        |  DataExtractionAgent (Python) |
        |  - Async API Calls            |
        |  - Cleans and standardizes    |
        +---------------+---------------+
                        |
                        v
       +-------------------------------+
       | ComparableDiscoveryAgent      |
       | - Similarity scoring engine   |
       +---------------+---------------+
                       |
                       v
            +---------------------+
            | Flask REST API      |
            | - /api/properties   |
            | - /api/analyze/...  |
            +---------------------+
                       |
                       v
          +----------------------------+
          | Frontend (Next.js + Tailwind) |
          +----------------------------+

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🧪 Why Mock Data?

Working with real county data APIs can be tough:

• Some require API keys or legal agreements

• Rate-limiting kills dev speed

• Privacy and licensing concerns

Mock data solves all of this during dev and testing. You can switch to real APIs later by editing just one class: DataExtractionAgent.

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🚀 Getting Started

git clone https://github.com/AyaanShaheer/property-analysis.git

Backend Setup

cd backend
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python app.py

Frontend Setup

cd frontend
npm install
npm run dev

Visit:

• Frontend: http://localhost:3000

• Backend API: http://localhost:5000

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📡 Example API Call

POST /api/analyze/comparables

{
  "property_id": "CO0001"
}

Or use property_data instead.

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🔒 Switching to Real APIs

Just update:

• APIDiscoveryAgent with real URLs and headers

• API_KEYS dict for secure keys

Ensure compliance with:

• API rate limits

• Licensing

• Privacy policies

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💥 Results Snapshot

Target Property: 2456 Industrial Blvd
Zoning: M1
Found 5 comparables:
 1. 9825 Industry Ave (Score: 0.91, High confidence)
 2. 4321 Logistic Dr (Score: 0.84, High confidence)
 3. ...

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🙌 What I Learned

• How to structure multi-agent backend systems

• Async data handling with aiohttp

• Building extensible similarity scoring logic

• Clean RESTful API design

• Tailwind + Next.js is an amazing combo!

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🚧 Next Steps

• Integrate real-time county APIs

• Add map visualization with Leaflet or Mapbox

• Build user auth & property bookmarking

• Dockerize and deploy

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📎 Project Links

• GitHub Repo: github.com/AyaanShaheer/property-analysis

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🧑‍💻 Contributors Welcome!

Want to help?

• Add new counties

• Improve frontend UI

• Build API error dashboards

Just fork the repo, send a PR, or DM me on Twitter!

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📝 License

MIT – This project was assigned by Starboard AI

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