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Jscrambler: Pioneering Client-Side Protection Platform
Jscrambler offers an exclusive blend of cutting-edge first-party JavaScript obfuscation and state-of-the-art third-party tag protection.

Jscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.

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Resco toolkit for building mobile apps
A no-code toolkit for building responsive and resilient mobile business applications for Microsoft Power Platform, Dynamics 365, Dataverse and Salesfo

Deploying mobile apps with Resco takes days, not months—all without writing a single line of code. Workers can download the Resco app from AppStore, Google Play, or Windows Store, log into your company environment, and instantly use the app you have published on any device.

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Revise.jl

Automatically update function definitions in a running Julia session

Revise.jl is a Julia package that automatically updates functions, types, and modules in a running Julia session when their source code changes. It significantly improves the development workflow by removing the need to restart the REPL or re-include files after edits. Revise is ideal for iterative coding, package development, and interactive exploration, enabling a fast and fluid programming experience.

Downloads: 0 This Week

Last Update: 2026-04-08
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2

Gen.jl

A general-purpose probabilistic programming system

An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language...

Downloads: 0 This Week

Last Update: 2025-07-11
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