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Showing 2 open source projects for "code editoral software"

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  • ShareCRM is an AI-powered enterprise CRM platform designed to connect data and teams across the entire customer lifecycle. Icon
    ShareCRM is an AI-powered enterprise CRM platform designed to connect data and teams across the entire customer lifecycle.

    Trusted by 6000+ Large and Medium Enterprises

    ShareCRM is an AI-powered, customizable and affordable enterprise CRM solution to seamlessly integrate and empower every aspect of your business.
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  • LinkSquares: All-in-One Contract Management Platform Icon
    LinkSquares: All-in-One Contract Management Platform

    #1 Customer Rated CLM Any Contract. Every Department. One Platform.

    LinkSquares is the leading Contract Lifecycle Management (CLM) software designed to help legal, procurement, and business operations teams master the entire contract lifecycle, from creation to execution and renewal. The platform transforms how companies manage agreements by centralizing data, automating routine work, and providing actionable insights powered by AI. This single, connected source of truth helps teams eliminate manual processes, streamline workflows, boost visibility, and ensure compliance across thousands of contracts, ultimately reducing risk and administrative burden.
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    DotVVM

    DotVVM

    Open source MVVM framework for Web Apps

    DotVVM is an open-source framework for ASP.NET. It lets you create web apps using the MVVM pattern, with just C# and HTML. DotVVM can be used to build new ASP.NET Core web apps, or to modernize legacy ASP.NET apps and migrate them to .NET 5. Save your time with GridView, FileUpload and other components shipped with the framework. Don't spend the time building an API. Just load data from the database and use data-binding to display them. DotVVM needs less than 100 kB of JavaScript code. It's...
    Downloads: 1 This Week
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  • 2
    Lightly

    Lightly

    A python library for self-supervised learning on images

    A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training...
    Downloads: 0 This Week
    Last Update:
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