Product intelligence agent that turns live Amazon data plus Reddit sentiment into a purchase recommendation
An agent collects structured product data (price, rating, sellers, features, stock) from an Amazon listing via an API, then runs a keyword search on Reddit to capture real customer discussion about the same product, and finally passes both structured datasets to an LLM that produces an explained buy/don't-buy recommendation. The point is that the agent needs fresh, structured evidence gathered at query time rather than relying on pre-trained knowledge or a RAG index.
online BOTH AI Agents & Automation
From AI Engineer — Building AI Agents with Real-Time Web Data — Yohan Raju, Bright Data at 01:17
Problem: An LLM alone can't see current prices, stock levels or real user sentiment, and AI crawlers are often blocked by robots.txt and anti-bot systems, so agents get stale or no data exactly when freshness matters.
For: Shoppers, affiliates or e-commerce analysts who want evidence-based purchase recommendations; the same collect-then-analyze pattern generalizes beyond e-commerce to any domain where live web data plus public sentiment informs a decision.
Products from this video
Bright Data APIs Bright Data MCP Server Bright Data Web Unlocker and Browser API Claude Code Gemini Google Colab
Examples
- The workshop's own demo: Amazon tumbler listing + Reddit sentiment → 'yes, buy it' recommendation citing positive reviews, discount and low stock
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