Real Estate Property Report Compiler

From fragmented property data to polished, professional marketing packets in seconds

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Inspiration

Real estate agents spend countless hours creating marketing packets for buyers and sellers. They manually gather MLS data, market trends, neighborhood stats, and property photos, then format them into something client-facing. The process is slow, error-prone, and inconsistent. We wanted to automate this workflow and show how Foxit’s APIs can turn messy, fragmented property data into polished, professional Real Estate Marketing Packets in seconds.

What We Learned

Working on this project showed us how powerful chained API workflows can be. We learned how to use the Foxit Document Generation API to convert structured HTML into reports, and then enhance them with the Foxit PDF Services API to compress, merge, and finalize the output. We also deepened our understanding of data scraping, formatting challenges, and workflow design.

How We Built It

  • Scraping: Extracted property details (price, address, attributes, images) from listing pages.
  • Data Enrichment: Pulled in neighborhood statistics and market trends.
  • HTML Generation: Built structured HTML templates for property reports.
  • Foxit Document Generation API: Converted HTML → DOCX → PDF.
  • Foxit PDF Services API: Compressed, merged, and optimized the PDFs into client-ready marketing packets.

Challenges

  • Inconsistent HTML structure across property pages made scraping difficult.
  • Translating raw HTML into clean, professional PDFs required iteration.
  • Chaining multiple APIs together without breaking the workflow took debugging.

In the end, we built a tool that doesn’t just work for a hackathon — it could actually be used by real estate agents today.

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