
Oxylabs is a market leader in web intelligence, helping businesses worldwide turn public web data into actionable insights with enterprise-grade, ethical, and compliant solutions.
Its proxy infrastructure spans one of the largest global networks, offering residential, ISP, mobile, datacenter, and dedicated datacenter proxies, along with Web Unblocker – an AI-driven tool that ensures seamless, block-free access to even the most protected sites.
On the scraping side, Oxylabs provides a complete ecosystem. The Web Scraper API manages every stage of large-scale data extraction, from proxy management to parsing, while OxyCopilot, an AI-powered assistant, generates parsing requests from simple natural language prompts. For dynamic, bot-protected websites, the Headless Browser, a headless browser designed to mimic human behavior, ensures uninterrupted access.
Oxylabs also pioneers AI-driven tools like AI Studio, which enables natural language scraping and crawling so anyone can extract data without writing code. Its ready-made datasets provide instant, structured information across industries such as e-commerce, real estate, travel, and more – accelerating data projects without custom scraping.
With the largest proxy services in the market, Oxylabs offers 177M+ IPs across 195 countries and is trusted by 4,000+ clients worldwide, including Fortune 500 companies. Plus, their 24/7 customer service ensures businesses get support whenever it’s needed.
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LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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Parsebridge
Parsebridge is an innovative PDF parsing API designed to convert PDFs into well-structured Markdown format. This tool efficiently extracts text, tables, and various data from PDF files, catering specifically to developers who require dependable document parsing capabilities at scale. It can adeptly manage complex PDFs, including those with intricate tables, multi-column layouts, nested structures, and scanned pages—all within a single API call, effectively transforming challenging elements that often confuse other parsers into usable Markdown. With the ability to accurately parse merged cells, nested headers, and sophisticated layouts, users can expect clear and precise outputs rather than jumbled results. Additionally, Parsebridge offers the convenience of live testing, allowing users to either paste a PDF URL or upload a document directly to the preview page to generate Markdown without the need for an account. Currently, it exclusively supports PDF files, prioritizing high extraction quality for documents up to 100MB in size. Utilizing Docling, an open-source parser renowned for its excellence in table extraction and layout preservation, Parsebridge manages the necessary infrastructure, OCR, scaling, and the API layer, ensuring a seamless user experience. This comprehensive approach makes Parsebridge a valuable tool for anyone needing reliable PDF parsing solutions.
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DeepTagger
DeepTagger is an innovative, no-code platform that utilizes artificial intelligence to transform various document types, such as PDFs, images, and Word files, into organized and actionable data using a user-friendly "highlight-and-label" system. Users simply upload their documents, select the relevant data points, and train the model through examples instead of relying on rigid templates, after which they can execute predictions, export their findings, and improve accuracy. The platform is designed to manage intricate structures, such as line items within invoices and tables within other tables, while also accommodating scanned documents and low-resolution images thanks to its powerful optical character recognition (OCR) capabilities. Additionally, DeepTagger includes functionalities for splitting multi-document PDFs, understanding intent and context, and position-aware extraction to differentiate repeated phrases for more precise data retrieval. Its pricing model is based on usage and offers a free tier for processing up to 200 documents, while higher subscription levels provide access to enhanced features, including batch prediction, nested schemas, priority support, a multi-tenant architecture, and compliance suitable for enterprise needs. Overall, DeepTagger stands out as a versatile solution for those looking to streamline their document processing and data extraction workflows.
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