BrowserAct vs Handinger

BrowserAct is an AI-powered web scraping tool that lets you extract data from any website without writing code. It uses natural language prompts to create browser automation workflows, making it accessible for marketers, researchers, and analysts who need reliable data fast. The platform handles complex site obstacles like pop-ups, CAPTCHAs, and geo-restrictions by mimicking human browsing behavior, ensuring smooth and uninterrupted scraping.

This tool runs your scraping tasks continuously on a cloud platform, so your workflows operate 24/7 without downtime or maintenance. It integrates easily with popular automation tools like n8n, Make, and Zapier, allowing you to connect web data directly into your business processes. BrowserAct also offers a marketplace with ready-made templates and a community for sharing and improving workflows.

BrowserAct’s dual-mode data capture combines AI-driven browser automation with traditional scraping methods to deliver accurate, hallucination-free data. It automatically switches between large language models and standard scrapers to optimize speed and cost. The platform supports global IP routing, enabling you to gather region-specific information effortlessly.

The team behind BrowserAct has years of experience in robotic process automation and web automation, focusing on making data acquisition simple, affordable, and accessible for everyone. Whether you want to track prices, monitor brand mentions, or automate research, BrowserAct provides a no-code, scalable solution that adapts to any website and use case.

Overall, BrowserAct stands out by offering a reliable, always-on scraping service that requires no coding skills, integrates with your existing tools, and supports a growing ecosystem of templates and community-driven workflows.

Handinger is a straightforward API that extracts website content without requiring any coding skills. It delivers website data in markdown format, making it ideal for training AI models or building AI agents. The tool also extracts structured metadata, images, and screenshots, supporting use cases like classification, enrichment, and visual AI training. It can handle JavaScript and React-rendered sites, expanding its reach to modern web pages. Users can upload lists of URLs or input single links, optionally adding AI prompts to extract specific information from any website. Handinger is designed for a broad audience, including AI developers, marketers, and anyone building AI workflows or knowledge bases. Its all-in-one approach manages browsers, proxies, and anti-bot measures, so users don’t have to worry about technical details. The pricing is simple and usage-based, with the first 1,000 requests free and no upfront costs. This makes it accessible for small projects and scalable for larger ones. Handinger also supports reading data from PDFs, Excel, and CSV files, broadening its data extraction capabilities. The clean output is optimized for easy integration with AI agents and workflows, helping users automate data collection and analysis. Overall, Handinger offers an affordable, easy-to-use solution for extracting web content and structured data to power AI applications and personal knowledge management.