
Gaffa is a REST API built for web scraping and browser automation, allowing developers to run real, full browsers at scale with a single API call. It removes the difficulty of managing headless browser frameworks, rotating proxies, CAPTCHA solving, and scaling infrastructure, all of which are handled automatically.
JavaScript-heavy and dynamic websites render exactly as they would for a human visitor by default. Beyond standard scraping, Gaffa supports AI-driven structured data extraction (extract data into a defined schema without writing CSS selectors), screenshot and PDF capture, infinite-scroll and form-filling automation, and clean Markdown conversion for feeding webpages directly into LLM and RAG pipelines.
A rotating residential proxy network keeps access reliable across regions, and a credit-based pricing model means teams pay only for the browser time and bandwidth they actually use. Gaffa is designed for AI engineers, data teams, and developers who want production-grade web data extraction without having to build and maintain their own infrastructure.
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Apify provides the infrastructure developers need to build, deploy, and monetize web automation tools. The platform centers on Apify Store, a marketplace featuring 10,000+ community-built Actors. These are serverless programs that scrape websites, automate browser tasks, and power AI agents.
Developers create Actors using JavaScript, Python, or Crawlee (Apify's open-source crawling library), then publish them to the Store. When other users run your Actor, you earn money. Apify manages the infrastructure, handles payments, and processes monthly payouts to thousands of active developers.
Apify Store offers ready-to-use solutions for common use cases: extracting data from Amazon, Google Maps, and social platforms; monitoring prices; generating leads; and much more.
Under the hood, Actors automatically manage proxy rotation, CAPTCHA solving, JavaScript-heavy pages, and headless browser orchestration. The platform scales on demand with 99.95% uptime and maintains SOC2, GDPR, and CCPA compliance.
For workflow automation, Apify connects to Zapier, Make, n8n, and LangChain. The platform also offers an MCP server, enabling AI assistants like Claude to discover and invoke Actors programmatically.
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CrowdRender
Render Farms utilize multiple computers to speed up the process of rendering 3D animations or static images. With our software, you can easily establish a render farm using your existing hardware, significantly cutting down on your rendering times. Simply connect two or more computers to the same Wi-Fi or Ethernet network, and you’ll be able to achieve faster rendering results without any hassle. Our user-friendly software is designed for easy installation with just one click, eliminating the need for any technical expertise or complex configurations. It fully supports rendering in Blender, compatible with the Cycles engine, and also allows for EEVEE rendering. Our add-on features seamless integration with Blender for a smooth workflow. Additionally, we provide updated time series data on product listings from NewEgg for selected GPU products from various manufacturers every two weeks to keep you informed. By utilizing our management portal, you can quickly install software across all your computers and deploy updates or new applications to all nodes with just a few clicks. This not only saves you time but also reduces costs on cloud storage and computing services, making it an economical choice for your rendering needs. Furthermore, our solution ensures that you can maximize your productivity without the headaches often associated with software management.
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SheepIt Render Farm
When a project owner submits their work to the queue, the service divides the animation into individual frames for rendering, dispatching each frame to a connected machine while optimizing its selection based on the available memory and CPU/GPU capabilities. Users can submit an unlimited number of projects, but only two renderings can occur simultaneously to prevent any one individual from overwhelming the render farm with excessive submissions. In instances where the render farm experiences congestion, this limit may be reduced to just one active rendering, a situation that occurs infrequently, typically just a few times each year. This careful management ensures efficient use of resources while maintaining fair access for all users.
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