Olostep
Olostep is a web-data API platform built for AI and developer use, enabling fast, reliable extraction of clean, structured data from public websites. It supports scraping single URLs, crawling an entire site’s pages (even without a sitemap), and submitting batches of up to ~100,000 URLs for large-scale retrieval; responses can include HTML, Markdown, PDF, or JSON, and custom parsers let users pull exactly the schema they need. Features include full JavaScript rendering, use of premium residential IPs/proxy rotation, CAPTCHA handling, and built-in mechanisms for handling rate limits or failed requests. It also offers PDF/DOCX parsing and browser-automation capabilities like click, scroll, wait, etc. Olostep handles scale (millions of requests/day), aims to be cost-effective (claiming up to ~90% cheaper than existing solutions), and provides free trial credits so teams can test its APIs first.
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Crawl4AI
Crawl4AI is an open source web crawler and scraper designed for large language models, AI agents, and data pipelines. It generates clean Markdown suitable for retrieval-augmented generation (RAG) pipelines or direct ingestion into LLMs, performs structured extraction using CSS, XPath, or LLM-based methods, and offers advanced browser control with features like hooks, proxies, stealth modes, and session reuse. The platform emphasizes high performance through parallel crawling and chunk-based extraction, aiming for real-time applications. Crawl4AI is fully open source, providing free access without forced API keys or paywalls, and is highly configurable to meet diverse data extraction needs. Its core philosophies include democratizing data by being free to use, transparent, and configurable, and being LLM-friendly by providing minimally processed, well-structured text, images, and metadata for easy consumption by AI models.
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HyperCrawl
HyperCrawl is the first web crawler designed specifically for LLM and RAG applications and develops powerful retrieval engines. Our focus was to boost the retrieval process by eliminating the crawl time of domains. We introduced multiple advanced methods to create a novel approach to building an ML-first web crawler. Instead of waiting for each webpage to load one by one (like standing in line at the grocery store), it asks for multiple web pages at the same time (like placing multiple online orders simultaneously). This way, it doesn’t waste time waiting and can move on to other tasks. By setting a high concurrency, the crawler can handle multiple tasks simultaneously. This speeds up the process compared to handling only a few tasks at a time. HyperLLM reduces the time and resources needed to open new connections by reusing existing ones. Think of it like reusing a shopping bag instead of getting a new one every time.
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UseScraper
UseScraper is a powerful web crawler and scraper API designed for speed and efficiency. By entering any website URL, users can retrieve page content in seconds. For those needing comprehensive data extraction, the Crawler can fetch sitemaps or perform link crawling, processing thousands of pages per minute using the auto-scaling infrastructure. The platform supports output in plain text, HTML, or Markdown formats, catering to various data processing needs. Utilizing a real Chrome browser with JavaScript rendering, UseScraper ensures the successful processing of even the most complex web pages. Features include multi-site crawling, exclusion of specific URLs or site elements, webhook updates for crawl job status, and a data store accessible via API. The service offers a pay-as-you-go plan with 10 concurrent jobs and a rate of $1 per 1,000 web pages, as well as a Pro plan for $99 per month, which includes advanced proxies, unlimited concurrent jobs, and priority support.
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