Branding
Real Estate Document Intelligence System
A Python XML-to-JSON transformation pipeline converting complex real estate appraisal documents into structured datasets, with OpenAI Vision APIs and LLM-based generative AI for automated metadata extraction and document intelligence.
Year :
2025
Industry :
AI / Data Engineering
Client :
Personal Project
Project Duration :
2 months
Problem :
Real estate appraisal documents are complex, unstructured XML formats that resist automated analysis. Extracting reliable metadata — property details, valuations, images — for downstream analytics requires a robust transformation and AI validation layer.
Solution :
Developed a Python XML-to-JSON transformation pipeline converting complex appraisal documents into structured datasets, enabling automated data engineering and reliable metadata extraction at operational scale. Integrated OpenAI Vision APIs and LLM-based generative AI to analyze property images and automate metadata extraction for NLP-driven document intelligence.
Tech Stack :
Python · XML-to-JSON · OpenAI Vision APIs · LLM Generative AI · NLP · AI Validation · Data Engineering · Metadata Extraction
Impact :
The system enables automated data engineering and cross-functional analytics workflows at operational scale. AI validation checks ensure output security and reliability, making the pipeline suitable for production deployment in document intelligence applications.
