Developer Builds AI Agent to Automate Real Estate Comps, Shares What Works
A real estate investor and developer documented their hands-on experience building an AI agent to automate property comparable analysis, a process traditionally requiring hours of manual spreadsheet work. Early attempts using a basic LangChain agent with web scraping tools repeatedly failed with silent timeouts and no useful output. Switching to LangGraph provided more structured control by defining explicit states for data retrieval, filtering, adjustment calculation, and report generation. The developer also experimented with CrewAI's multi-agent setup, separating data analysis and property valuation roles, though this introduced additional failure points. Key lessons included building robust edge-case handling, structured JSON outputs, and pre-filtering steps to reduce API token costs.
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