From Spreadsheet to AI Assistant: How We Built a Self-Updating RAG Agent for Property Queries
I've just deployed Cole Medin's Agentic RAG system for our real estate database, with some custom modifications worth sharing: What it does: ๐ ๐ Creates a dynamic knowledge base that auto-updates whenever source spreadsheets change ๐ฌ Handles complex natural language queries across your data ("Find products with specific features" or "Compare items matching certain criteria") ๐ฑ Powers customer-facing interactions through QR codes, websites, or messaging platforms ๐ Returns precisely formatted responses with accurate links and only the most relevant details ๐ Works for any industry with structured data - real estate, e-commerce, inventory management, service catalogs, product specifications, or company knowledge bases What makes this system awesome: โจ ๐ง It's super smart: It knows when to search for information, when to do math, and when to grab the whole documentโjust like knowing when to use different tools for different jobs ๐ It reads entire documents when needed: Instead of just looking at random pages, it can read the whole document to understand everything ๐ข It's great at math problems: It can calculate numbers from spreadsheets without making mistakes ๐งฉ It connects the dots: It can find information that's spread across different files and put it togetherโlike solving a puzzle ๐ It handles lots of files at once: You don't have to upload one file at a time; it works with all your information together ๐พ It saves space: It stores all your information in a clever way that doesn't waste computer memory Technical implementation: โ๏ธ ๐ ๏ธ Built on Assistable using Cole's n8n workflow template ๐ Modified with custom SQL queries for property-specific lookups ๐ค Using ADA-002 for embeddings and GPT-4.0 for responses (Claude Opus seemed slower) ๐๏ธ Supabase backend with 4000 token chunks and zero overlap ๐ฃ๏ธ Text and voice response formats with separate prompts for each Challenges faced: ๐ง ๐ Ensuring links remain functional through vectorization ๐ Finding the right chunking strategy for property data