QuickLens

QuickLens is a real-time q-commerce intelligence system built on two autonomous agentic AI loops — one reactive, one proactive — powered by Bright Data's live web data infrastructure. THE PROBLEM Q-commerce prices on Blinkit, Zepto and Swiggy change multiple times a day. Consumers overpay without knowing it. Brands have zero visibility into competitor moves in real time. THE SOLUTION Consumer Loop (reactive): User asks "cheapest 1L Amul Milk in Indiranagar." The agent plans which platforms to query, calls Bright Data's Search API in one batch call across all 3 platforms, observes results, handles failures, and returns a ranked price comparison with delivery times and savings — in under 25 seconds. Brand Loop (proactive): Runs every 5 minutes without being asked. Monitors competitor SKUs, detects price drops and OOS events, reasons about signal significance, and fires natural language alerts with action recommendations — e.g. "Zepto OOS on Tata Salt 500g — boost Blinkit ad spend for next 2 hours." HOW BRIGHT DATA POWERS IT Direct scraping of q-commerce platforms is blocked by bot detection and JS rendering. Bright Data's search_engine_batch is the only viable path — querying all 3 platforms simultaneously in one call. scrape_batch fires as secondary enrichment when SERP snippets lack prices. Bright Data is the foundation, not an add-on. ARCHITECTURE Both loops share a Bright Data tool layer and Gemini 2.5 Flash Lite as reasoning engine. Shared state.json persists price history, watchlist, and alert log. APScheduler runs the brand loop as a background daemon so Streamlit stays responsive. TECH STACK Python · Gemini 2.5 Flash Lite · Bright Data MCP · Streamlit · APScheduler · Pydantic