Collect Web Data for AI & LLMs
Accurate, large-scale training data is essential for powering large language models (LLMs) and other machine learning systems. Our web intelligence solutions simplify large-scale data collection, enabling AI models to achieve faster and more reliable performance.
Access web data hassle-free
Enable AI to act on the web
Fuel models with real-time insights
Enhance quality through video data
Unlock the web for AI
We unlock web data at scale so you can focus on what matters most – scaling your AI projects to the top.
Access web data hassle-free
LLMs need real-time web data for accurate answers, but accessing it is complex and often breaks with site changes or restrictions. Try a low-code suite of AI-powered apps, AI Studio, for quick web data delivery.
Enable AI to act on the web
AI agents must execute complex, multi-step web tasks without interruption, but modern web security and anti-bot systems often get in the way. Integrate Oxylabs' Unblocking Browser into your projects.
Fuel models with real-time insights
While AI developers excel at building models, web scraping can be a hurdle. Choose all-in-one scraping solutions, such as Web Scraper API, to collect real-time data for models on a large scale, hassle-free.
Enhance quality through video data
AI models improve with video data, but gathering it at scale is challenging due to its size, diversity, and real-time needs. Use Oxylabs' Video Data Collection solutions to gather video insights effortlessly.
Let’s talk about your data needs and how they can fuel AI development
Web intelligence solutions for your needs
From proxies and headless browsers to low-code platforms and all-in-one scraping solutions, Oxylabs has you covered.
All-in-one web scraping solutions for real-time insights
Web Scraper API is a powerful web data gathering solution, helping AI developers avoid getting blocked and collect real-time web data on a large scale, allowing them to focus on boosting the reliability and accuracy of their AI projects.
Collect real-time data from popular search engines
Access and gather cashed search data to leverage stored copies
Get information delivered in Markdown output
Model Context Protocol (MCP) integration with Web Scraper API
MCP integration with Web Scraper API delivers structured, AI-ready web data with proper context, metadata, and well-formatted instructions, making it easy for LLMs to use effectively.
AI-powered apps for hassle-free web scraping
AI Studio makes web data collection fast, simple, and accessible. Just describe what you need in natural language, and our AI-powered apps navigate websites seamlessly, delivering structured, LLM-ready data.
Simplify your workflow with a low-code solution
Connect effortlessly to AI models or real-time apps
Access complex websites without interruptions
Advanced headless browser for human-like web actions
Unblocking Browser is a headless browser for automation, testing, and scraping. Enable AI agents to mimic real user behavior, allowing them to efficiently perform multi-step tasks, such as browsing, navigating, clicking, and similar actions.
Simulate human-like interactions with built-in stealth features
Automate web interactions using Claude or Cursor via MCP
Integrate easily Puppeteer, Playwright, and CDP-compatible libraries
Multimodal data for enhanced quality
Fast and reliable video data collection for training LLMs and boosting reliability.
High-Bandwidth Proxies
High-speed and low-latency proxies for uninterrupted video data scraping
Video Data API
Advanced scraper for high-volume video data extraction with native cloud/OSS support
Video datasets
Creator-approved, scalable, and ethical video datasets for enhancing AI output
Certified data centers and upstream providers
All of our products are insured
All of our products are covered by Technology Errors & Omissions (Technology E&O) and Cyber Insurance.
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Frequently asked questions
AI training data is the material used to train machine learning models. It's the foundation of any AI model. After studying such data, an AI model can recognize patterns and make predictions.
The quality and quantity of AI training data directly impact the model's performance and accuracy. Properly curated and labeled AI training data helps build reliable systems.
AI training requires large volumes of data, disqualifying the traditional hands-on data acquisition methods. Here are the four ways you can source AI training data for machine learning:
Scraping web data with automated means from public websites.
Acquiring AI training datasets from third-party providers.
Generating synthetic training data using graphics engines.
Partnering with businesses willing to share their proprietary data.
See this article about the main public data sources for LLM training to learn more on this topic as well as take a look into what is LLM. You can also use already pre-trained LLMs, such as GPT-4.5 and similar, allowing you to save time and resources. See this CrewAI and Web Scraper API integration to see how you can easily build your own AI agents, and check out our tutorial on how to scrape Google AI Mode.
The actual data volumes for machine learning are highly dependent on the specific use case. The best approach is to start with existing benchmarks and gradually scale up as necessary.
Generally, you can try to predict your AI training data needs.
Small models (simple tasks): 100s to 1,000s of examples:
Spam filters
Website guidance (recommendations)
Voice assistants
Medium models (moderately complex tasks): 10,000s to 100,000s of examples:
Natural language processing (chatbots)
Facial recognition for smartphones
Translators
Large models (highly complex tasks): millions of examples:
Generative AI
Autonomous driving
Robotics
With Oxylabs solutions, you get collected data in either structured JSON or raw HTML format. For datasets, we provide AI training data in the format of your choice.
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