A Privacy-First Local Price Comparator (Open-Source AI Side Hustle)

Description and use

A local AI price comparator that keeps user data private by running entirely on the user’s machine.

Problem

Users want to compare prices across e-commerce sites without exposing their browsing history and personal data to third‑party services.

Outcome

The tool enables privacy‑conscious shoppers to compare prices locally, eliminating data leakage to external services.

Workflow

• 1. User inputs a product URL into the tool.
• 2. Tool scrapes the raw HTML of the product page using standard Python scraping libraries.
• 3. Local AI model (open‑weight, e.g., Google’s Gemma) parses the HTML, extracts price, shipping cost, and product specs.
• 4. Model outputs a clean JSON comparison for the user.
• 5. All processing occurs locally; no data leaves the user’s machine.

Evidence

Most popular price‑tracking extensions operate on a data theft model: they give you discounts, but they harvest your browsing history, shopping habits, and personal profiles to sell to advertisers.

Source

Instead of relying on centralized APIs that log user queries, this project uses local inference.

Source

The local AI model is prompted to parse the messy HTML, extract the exact price, shipping costs, and product specs, and output a clean JSON comparison—all without any data ever pinging an external server.

Source