🚗 I built a Conversational Car Marketplace powered by LLMs

Edward Obar Cabigting — Mon, 04 May 2026 05:05:26 +0000

Most car platforms still rely on rigid filters.
I wanted to explore something better:
👉 What if users could just talk to the system?
So I built a platform where you can type:
“BMW E92 under $20k, manual, 70 miles”
…and the system understands and returns relevant cars instantly.

🧠 What makes it interesting?
Instead of simple keyword matching, the system extracts structured data from natural conversation:

Core vehicle → make, model, generation
Time & usage → year range, mileage
Preferences → transmission, color
Market constraints → location, price range This allows transforming messy human language into precise database queries.

⚙️ Tech Stack

Next.js (frontend)
FastAPI (backend)
PostgreSQL (data layer)
LLM (intent + entity extraction)
Web scraping pipeline (real listings)

🔄 How it works

User enters natural language
LLM extracts structured fields
Backend converts to query filters
PostgreSQL returns matching vehicles
Results improve through conversation

💡 Why this matters
This approach replaces:
❌ Manual filters
❌ Trial-and-error search
With:
✅ Natural interaction
✅ Faster discovery
✅ Smarter recommendations

🚀 Try it here:
https://askdrive-web.vercel.app/
I’m exploring how LLMs can redefine search UX in marketplaces.
Would love to hear your thoughts or feedback👇

DEV Community: Edward Obar Cabigting

🚗 I built a Conversational Car Marketplace powered by LLMs