Product Feedback Analyzer
Real-Time AI Product Sentiment Analysis, Pain Point Extraction & Price Intelligence Engine.
How Nexis Insights Works — 3-Step AI Pipeline & Core Benefits
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Paste any raw customer reviews or an e-commerce product link (Amazon, Myntra, Flipkart, Croma). Our AI engine extracts genuine buyer sentiments, filters out fake promotional noise, and calculates real category price intelligence.
🌐 Smart Web Scraping
Scrapes JSON-LD product price metadata, images, and live customer reviews from top retail stores.
🔮 Deep AI Analysis
NVIDIA Nemotron 550B analyzes sentiment %, aggregates key pain points & feature requests.
📊 Price & SQLite Logging
Compares category competitor prices, plots 6-month trends & saves report to your WASM database.
Zero Fake Reviews
Filters out paid influencer fluff to give you raw, unedited buyer feedback.
Anti-Price Gouging
Identifies fake discounts and alerts you when a product is actually at its lowest historical price.
Local WASM SQLite
Your history is saved in an embedded browser database (`sql.js`), 100% private and CSV exportable.
Input Feedback Data / Product URL
NVIDIA Nemotron 550BQuick Analytics
SQLite Persistence🧠 Ask RAG AI Engine
Perform semantic vector queries & natural language Q&A across your indexed customer feedback database with grounded citations.
🔍 Ask Anything About Your Customer Data
Vector Search📥 Index Raw Feedback Batch
WASM Vector Store📌 Retrieved Source Citations & Match Confidence
Top-K Cosine MatchesAnalysis History
View past product reports saved to your persistent SQLite database.
🛒 Unified Quick-Commerce Cart
Compare prices across Blinkit, Zepto, Instamart & BigBasket — find the cheapest, fastest, or split-cart option.
📝 Your Grocery List
Bulk Paste ModeSystem & AI Settings
Configure AI model engine, web scraper options, and database preferences.
🤖 AI Engine Configuration
Connected🌐 Web Scraper & Price Engine
Active🗄️ SQLite WASM Database Status
nexis_insights.dbYour records, price histories, and user sessions are securely persisted in local WASM SQLite database.