List of Octave Integrations

This is a list of platforms and tools that integrate with Octave. This list is updated as of February 2026.

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    Rayven Reviews & Ratings

    Rayven

    Turn fragmented operational data into automation and made-to-fit operational solutions.
    Rayven designs and delivers operational systems for industrial and asset-intensive businesses. We connect fragmented data from IT, OT, IoT, files, and existing systems - anything - without rip-and-replace, then turn it into automation and operational applications that run in one place. Rayven replaces spreadsheets, manual processes, and disconnected tools with systems built around how operations actually run - across sites, assets, and teams. Customers get real-time visibility, automated workflows, and practical systems that work in industrial environments. Everything is delivered end-to-end, including the underlying technology. Rayven works directly with customers and through partners via white-label and co-branded solutions. Based in Australia and New Zealand, working globally.
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    Overleaf Reviews & Ratings

    Overleaf

    Overleaf (Writelatex Limited)

    Effortlessly collaborate on LaTeX documents from anywhere.
    Setting up LaTeX is an easy task, and you can start working with it right away, no matter your experience level. Overleaf offers a comprehensive LaTeX platform hosted on their servers, providing instant availability. By using Overleaf, you maintain a uniform LaTeX configuration regardless of your location, which is especially advantageous for teamwork with peers and students, removing any chances of version mismatches or package issues. This smooth integration enhances the overall workflow, making it more efficient and productive for all participants. Additionally, Overleaf's collaborative features allow multiple users to work on the same document simultaneously, further streamlining the process.
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    JupyterLab Reviews & Ratings

    JupyterLab

    Jupyter

    Empower your coding with flexible, collaborative interactive tools.
    Project Jupyter is focused on developing open-source tools, standards, and services that enhance interactive computing across a variety of programming languages. Central to this effort is JupyterLab, an innovative web-based interactive development environment tailored for Jupyter notebooks, programming, and data handling. JupyterLab provides exceptional flexibility, enabling users to tailor and arrange the interface according to different workflows in areas such as data science, scientific inquiry, and machine learning. Its design is both extensible and modular, allowing developers to build plugins that can add new functionalities while working harmoniously with existing features. The Jupyter Notebook is another key component, functioning as an open-source web application that allows users to create and disseminate documents containing live code, mathematical formulas, visualizations, and explanatory text. Jupyter finds widespread use in various applications, including data cleaning and transformation, numerical simulations, statistical analysis, data visualization, and machine learning, among others. Moreover, with support for over 40 programming languages—such as popular options like Python, R, Julia, and Scala—Jupyter remains an essential tool for researchers and developers, promoting collaborative and innovative solutions to complex computing problems. Additionally, its community-driven approach ensures that users continuously contribute to its evolution and improvement, further solidifying its role in advancing interactive computing.
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    CoppeliaSim Reviews & Ratings

    CoppeliaSim

    Coppelia Robotics

    Unleash robotics innovation with unparalleled simulation versatility today!
    CoppeliaSim, developed by Coppelia Robotics, is a highly versatile and powerful simulator for robotics, catering to a multitude of applications including rapid algorithm development, factory automation modeling, swift prototyping, verification, educational uses in robotics, remote monitoring, safety assessments, and the creation of digital twins. Its architecture is designed for distributed control, enabling the individual management of objects and models through embedded scripts in languages such as Python and Lua, C/C++ plugins, and remote API clients that accommodate various programming languages like Java, MATLAB, Octave, C, C++, and Rust, alongside customized solutions. The simulator's compatibility with five distinct physics engines—MuJoCo, Bullet Physics, ODE, Newton, and Vortex Dynamics—allows for rapid and customizable computations of dynamics, resulting in highly realistic simulations that accurately depict physical interactions, including collision responses, grasping actions, and the dynamics of soft bodies, strings, ropes, and fabrics. Moreover, CoppeliaSim supports both forward and inverse kinematics for an extensive array of mechanical systems, significantly enhancing its applicability across different robotics domains. This unique combination of flexibility and functionality positions CoppeliaSim as an invaluable resource for both researchers and industry professionals in the robotics sector, driving innovation and development in this rapidly evolving field.
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    Bayesforge Reviews & Ratings

    Bayesforge

    Quantum Programming Studio

    Empower your research with seamless quantum computing integration.
    Bayesforge™ is a meticulously crafted Linux machine image aimed at equipping data scientists with high-quality open source software and offering essential tools for those engaged in quantum computing and computational mathematics who seek to leverage leading quantum computing frameworks. It seamlessly integrates popular machine learning libraries such as PyTorch and TensorFlow with the open source resources provided by D-Wave, Rigetti, IBM Quantum Experience, and Google's pioneering quantum programming language Cirq, along with a variety of advanced quantum computing tools. Notably, it includes the quantum fog modeling framework and the Qubiter quantum compiler, which can efficiently cross-compile to various major architectures. Users benefit from a straightforward interface to access all software via the Jupyter WebUI, which features a modular design that supports coding in languages like Python, R, and Octave, thus creating a flexible environment suitable for a wide array of scientific and computational projects. This extensive setup not only boosts efficiency but also encourages collaboration among professionals from various fields, ultimately leading to innovative solutions and advancements in research. As a result, users can expect an integrated experience that significantly enhances their analytical capabilities.
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