The Problem: Keyword search fails for complex, multi-item projects. If I want to "build a backyard rink" or "draft-proof my house," I usually end up with 15 tabs open, manually piecing together a shopping list from forums and reviews.
The Solution: I built an intent-based search engine. instead of matching keywords, it converts user prompts into vector embeddings to map broad goals (intents) to specific product clusters.
The Stack:
Backend: node.js/TypeScript
Search: pgvector for semantic similarity (PostgreSQL)
LLM: Orchestrates the "logic" of the project plan and validates compatibility.
The "Microsoft" Context: I actually launched this 24 hours before Microsoft Copilot released their "Shopping Agent." While I can't compete with them on generic "buy a laptop" queries, I’m pivoting to go deep on complex DIY/Hardware projects where context matters more than reach.
Current Status: Currently indexing Amazon (US/CA) with every search. My internal prototype worked perfectly with Canadian Tire (local hardware inventory is much better for DIY than Amazon), and I'm working on deep-linking that next to build better carts.
I’d love feedback on the result relevance. Roast my MVP.
Show HN: LogiCart – Intent-based shopping agent built with pgvector · HackerTrans
The Problem: Keyword search fails for complex, multi-item projects. If I want to "build a backyard rink" or "draft-proof my house," I usually end up with 15 tabs open, manually piecing together a shopping list from forums and reviews.
The Solution: I built an intent-based search engine. instead of matching keywords, it converts user prompts into vector embeddings to map broad goals (intents) to specific product clusters.
The Stack:
Backend: node.js/TypeScript
Search: pgvector for semantic similarity (PostgreSQL)
LLM: Orchestrates the "logic" of the project plan and validates compatibility.
The "Microsoft" Context: I actually launched this 24 hours before Microsoft Copilot released their "Shopping Agent." While I can't compete with them on generic "buy a laptop" queries, I’m pivoting to go deep on complex DIY/Hardware projects where context matters more than reach.
Current Status: Currently indexing Amazon (US/CA) with every search. My internal prototype worked perfectly with Canadian Tire (local hardware inventory is much better for DIY than Amazon), and I'm working on deep-linking that next to build better carts.
I’d love feedback on the result relevance. Roast my MVP.