Best AI Math Solvers for Microsoft Excel

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Compare the Top AI Math Solvers that integrate with Microsoft Excel as of October 2025

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This a list of AI Math Solvers that integrate with Microsoft Excel. Use the filters on the left to add additional filters for products that have integrations with Microsoft Excel. View the products that work with Microsoft Excel in the table below.

What are AI Math Solvers for Microsoft Excel?

AI math solvers use technology to solve mathematical problems automatically. By using algorithms, they can take complex equations and break them down into simpler parts. AI math solvers are able to work quickly and accurately compared to traditional methods of solving mathematics. They are used in a variety of industries such as finance, engineering, and healthcare to help automate tedious tasks. Compare and read user reviews of the best AI Math Solvers for Microsoft Excel currently available using the table below. This list is updated regularly.

  • 1
    Gurobi Optimizer

    Gurobi Optimizer

    Gurobi Optimization

    With our powerful algorithms, you can add complexity to your model to better represent the real world, and still solve your model within the available time. Integrate Gurobi into your applications easily, using the languages you know best. Our programming interfaces are designed to be lightweight, modern, and intuitive, to minimize your learning curve while maximizing your productivity. Our Python API includes higher-level modeling constructs that make it easier to build optimization models. Choose from Anaconda Python distributions with pre-built libraries to support application development, Spyder for graphical development, and Jupyter for notebook-style development.
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  • 2
    Artelys Knitro
    Artelys Knitro is a leading solver for large-scale nonlinear optimization problems, offering a suite of advanced algorithms and features to address complex challenges across various industries. It provides four state-of-the-art algorithms: two interior-point/barrier methods and two active-set/sequential quadratic programming methods, enabling efficient and robust solutions for a wide range of optimization problems. Additionally, Knitro includes three algorithms specifically designed for mixed-integer nonlinear programming, incorporating heuristics, cutting planes, and branching rules to effectively handle discrete variables. Key features of Knitro encompass parallel multi-start capabilities for global optimization, automatic and parallel tuning of option settings, and smart initialization strategies for rapid infeasibility detection. The solver supports various interfaces, including object-oriented APIs for C++, C#, Java, and Python.
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