AI-Powered Property Acquisition Monitoring System Development
Orçamento: $3000.0
FIXED /
⭐ 5.00 (4)
India
python, machine-learning, computer-vision, docker, artificial-intelligence
We are looking for an experienced AI Engineer to build an automated platform that continuously monitors residential property listings across the United States and identifies potential investment opportunities.
The system should automatically analyze new listings, detect distressed or motivated seller properties using AI, and instantly notify us whenever a property matches our investment criteria.
This project is the first phase of a much larger AI-powered real estate acquisition platform. We are looking for someone who can build a production-ready solution and continue working with us on future enhancements.
Project Objectives
The application should:
Monitor newly listed residential properties from multiple listing sources.
Continuously scan listings throughout the day.
Analyze listing titles and descriptions using AI.
Use computer vision to analyze listing photos for signs of distressed properties.
Combine image analysis with text analysis to determine whether a property is a qualified investment opportunity.
Filter properties using customizable investment rules.
Automatically generate a confidence score for every qualified property.
Send instant notifications (SMS and/or Email) whenever a matching property is detected.
Notifications should include:
Property address
Asking price
MLS/Listing ID
Listing URL
Agent information
AI confidence score
Brief explanation of why the property matched
The goal is to receive alerts within approximately five minutes of a qualifying listing becoming available.
Preferred Technology
We're open to recommendations but expect the solution to involve technologies such as:
Python
OpenAI, Gemini, Claude, or similar LLMs
Computer Vision (OpenCV, YOLO, or equivalent)
Docker
PostgreSQL or another suitable database
REST APIs
Background workers and scheduling
Cloud deployment (AWS, Azure, or GCP)
You may use additional technologies if they improve performance, scalability, or reliability.
Data Sources
The system should integrate with reliable real estate listing providers or APIs.
We are open to recommendations regarding the most stable and scalable data source.
Please explain your proposed approach, licensing considerations, and expected reliability of the listing source.
Required Skills
We're looking for someone with experience in:
Python Development
AI & LLM Integration
Computer Vision
Image Processing
API Development & Integration
Cloud Deployment
Docker
PostgreSQL
Automation Systems
Production Application Development
Experience with real estate technology, MLS/IDX, or property datasets is a strong advantage.
Deliverables
The completed project should include:
Fully functional production-ready application
Clean and maintainable source code
Deployment documentation
Installation guide
Configuration files
Logging and monitoring
Error handling
API documentation
Instructions for future maintenance and expansion
Timeline
We'd like to begin immediately.
A working MVP should be delivered within the next few weeks, followed by iterative improvements if needed.
When Applying
Please include:
Similar AI or automation projects you've built
Computer Vision experience
Experience with LLMs
API integration examples
Real estate or MLS/IDX experience (if any)
Your recommended technical architecture
Estimated timeline
Questions or suggestions for improving the project
Success Criteria
The project will be considered successful when the system can:
Continuously monitor new property listings
Analyze both images and descriptions automatically
Correctly identify distressed or motivated seller opportunities
Apply customizable investment filters
Send instant notifications without manual intervention
Operate reliably 24/7 with minimal maintenance
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