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  • Award-winning proxy networks, AI-powered web scrapers, and business-ready datasets for download.
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    Award-winning proxy networks, AI-powered web scrapers, and business-ready datasets for download.


    How the world collects public web data

    Bright Data is a leading data collection platform, enabling businesses to collect crucial structured and unstructured data from millions of websites through our proprietary technology. Our proxy networks give you access to sophisticated target sites using precise geo-targeting. You can also use our tools to unblock tough target sites, accomplish SERP-specific data collection tasks, manage and optimize your proxy performance as well as automating all of your data collection needs.
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  • Evertune | Improve Your Brand's Visibility in AI Search Icon
    Evertune | Improve Your Brand's Visibility in AI Search

    For enterprise marketing teams looking for a platform to understand and influence how AI models like ChatGPT recommend their products or services.

    Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search across ChatGPT, AI Overview, Gemini, Claude and more.
    Learn More
  • 1
    KaibanJS

    KaibanJS

    JS-native framework for building and managing multi-agent systems

    JavaScript-native framework for building multi-agent AI systems. Multi-agent AI systems promise to revolutionize how we build interactive and intelligent applications. However, most AI frameworks cater to Python, leaving JavaScript developers at a disadvantage. KaibanJS fills this void by providing a first-of-its-kind, JavaScript-native framework designed specifically for building and integrating AI Agents. Harness the power of specialization by configuring AI agents to excel in distinct,...
    Downloads: 3 This Week
    Last Update:
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  • 2
    OSS-Fuzz Gen

    OSS-Fuzz Gen

    LLM powered fuzzing via OSS-Fuzz

    OSS-Fuzz-Gen is a companion project that helps automatically create or improve fuzz targets for open-source codebases, aiming to increase coverage in OSS-Fuzz with minimal maintainer effort. It analyses a library’s APIs, examples, and tests to propose harnesses that exercise parsers, decoders, or protocol handlers—precisely the code where fuzzing pays off. The system integrates with modern LLM-assisted workflows to draft harness code and then iterates based on build errors or low coverage signals. ...
    Downloads: 0 This Week
    Last Update:
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