Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 10 No 4 (2026): Volume 10, Issue 4, April 2026 | Pages: 193-197
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 16-04-2026
Traditional web scraping tools demand coding expertise, CSS selectors, and constant fixes when sites change, making them tough for students and researchers. We introduce scrapeFLOW, an intelligent no-code platform that combines AI automation with powerful node-based workflows for precise, in-depth data extraction from any website. Users can quickly query data in natural English via AI-powered FlowScrape (limited records via free APIs) or build complex workflows using React Flow editor with 34+ task nodes like Scraper (CSS selectors), Visualizer, Summarizer, Data Extractor, Filter, Enricher, and Scheduler – connecting nodes via edges for deep scraping, analysis, and automation. Built on Next.js 14, TypeScript, Prisma PostgreSQL, Firecrawl engine, and AI models (Claude suggestions, Llama-3.3 70B analysis), it delivers charts, ML predictions, JSON/CSV exports. Workflow mode enables unlimited precise scraping unlike prompt-based limits, scalable with paid APIs. This affordable system with Razorpay billing saves massive time for Indian students, turning websites into clean data effortlessly.
No-Code Scraping, Node Workflows, AI Insights, React Flow, Multi-Source Extraction, Visualizer Summarizer
Om Chaudhari, Bhavesh Choudhari, Vikrant Khaire, Nilesh Patil, & Prof. Manisha Hatkar. (2026). ScrapeFlow – No Code Workflow Based Web Scrapping SaaS Tool. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(4), 193-197. Article DOI https://doi.org/10.47001/IRJIET/2026.104027
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