Showing 5 open source projects for "mac browser"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

    Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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  • Turn traffic into pipeline and prospects into customers Icon
    Turn traffic into pipeline and prospects into customers

    For account executives and sales engineers looking for a solution to manage their insights and sales data

    Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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  • 1
    LWT ◆ Learning With Texts [Official]

    LWT ◆ Learning With Texts [Official]

    A feature-rich web application for language learning through reading

    LWT is a tool for Language Learning, inspired by: - Stephen Krashen's principles in Second Language Acquisition, - Steve Kaufmann's LingQ application, and - ideas from Khatzumoto - published at AJATT - All Japanese All The Time. You define languages you want to learn and import texts you want to use for learning. While listening to the audio (optional), you read the text, save, review and test words or multi-word expressions. In new texts all your previously saved words and expressions...
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    Downloads: 34 This Week
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  • 2

    treebolic-wordnet

    Treebolic hyperbolic visualization for WordNet

    WordNet Browser with Treebolic's hyperbolic rendering (see https://treebolic.sourceforge.net)
    Downloads: 0 This Week
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  • 3
    Hogan.js

    Hogan.js

    A compiler for the Mustache templating language

    Hogan.js is a 2.5k JS templating engine developed at Twitter. Use it as a part of your asset packager to compile templates ahead of time or include it in your browser to handle dynamic templates. If you're developing with Node.js, just use NPM to add the Hogan package. Hogan.js was developed against the mustache test suite, so everything that holds true for templates is also the case for hogan.js. That means you get variables, sections, lambdas, partials, filters, and everything else you've...
    Downloads: 0 This Week
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  • 4

    Language KISS HTML5

    Browser based flash cards

    Browser based flash cards to learn a language, see http://en.wikipedia.org/wiki/Flash_cards. You just need - a modern browser (smartphone, tablet, computer,...) and - an internet connection. Main features - learn (cards due to learn), swat (every card) - copy cards - filter - sort - synchronize between devices - share cards with other users (just use all and/or improve and add cards) Programm code and usage follows the KISS principle, see...
    Downloads: 0 This Week
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  • Create and run cloud-based virtual machines. Icon
    Create and run cloud-based virtual machines.

    Secure and customizable compute service that lets you create and run virtual machines.

    Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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  • 5
    LinqYedict

    LinqYedict

    Translate Chinese to English

    Translate Chinese to English using CEDICT (cantonese dictionary). Demonstrate the speed of C# and Linq. Copy the chinese text from any browser/application to Windows clipboard and see the translation.
    Downloads: 0 This Week
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