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AI-Powered Property Acquisition Monitoring System Development

Budget: $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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