Abstract
ExhibitorIQ is a full-stack, browser-based intelligent data extraction and event outreach platform that automates exhibitor data collection using multi-strategy web scraping, AI-powered catalog processing, email verification, and personalized campaign delivery. The system accepts trade show URLs, PDF catalogs, and uploaded spreadsheets, enabling multimodal data acquisition for a comprehensive exhibitor database. For URL-based inputs, the application employs a Playwright-driven headless browser stack with anti-bot evasion techniques including stealth fingerprinting, cookie persistence, proxy rotation, and Cloudflare bypass to extract exhibitor records from protected event websites. For PDF and image catalog inputs, the system leverages the Groq Vision API. Email validation is performed through format checking, disposable domain detection, MX record lookup, and optional Reoon API integration. The application is built using Python Flask, Pandas, BeautifulSoup4, openpyxl, and Playwright for a robust server-side architecture. By combining web scraping intelligence with AI document processing and automated campaign delivery, this system enhances event organizer productivity, data accuracy, and outreach efficiency in trade show management workflows.
Keywords
Exhibitor Data Extraction, Web Scraping, Anti-Bot Evasion, Playwright, Groq Vision AI, Email Verification, Event Management, Flask, Campaign Automation, PDF Processing, BeautifulSoup.
Citations
IRE Journals:
Surya J, Dr. K. Ponmozhi "ExhibitorIQ: Intelligent Exhibitor Data Extraction and Event Outreach Platform" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 2785-2791 https://doi.org/10.64388/IREV9I9-1715669
IEEE:
Surya J, Dr. K. Ponmozhi
"ExhibitorIQ: Intelligent Exhibitor Data Extraction and Event Outreach Platform" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715669
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