The article discusses applying a product thinking approach to real estate due diligence, focusing on interpreting seller disclosures and inspection documents.
It emphasizes the need to identify inconsistencies and hidden risks in real estate documents, noting the challenges faced by buyers under time pressure.
The author shares their personal experience of discovering issues post-closing that could have been caught with better document analysis.
They propose building a tool to flag potential document discrepancies, providing a second set of eyes for buyers.
The article highlights the importance of understanding the problem space and feasibility before market viability in product development.
Technical experiments using tools like ChatGPT and OCR revealed challenges in detecting document inconsistencies accurately.
The author explores the market potential for the proposed tool, considering factors like data consistency, customer retention, and core value proposition.
Ultimately, the article concludes that while the problem is real, the current market conditions and monetization model may not support the standalone product.
The author reflects on the project as a valuable learning experience in product discovery and knowing when to pivot focus.
The article invites connections from those working in risk assessment, document intelligence, or prop-tech fields and underscores the importance of problem-solving and user-centric design in product development.