From configuring model options to performing experiments on subscribed apps, there’s a whole lot more you can do in the Nextmv console to accelerate the development of your decision algorithms.
Shadow testing isn’t just for the MLOps crowd. Decision algorithm teams can have it too for their optimization models solving routing, scheduling, allocation, and fulfillment problems across supply chain, retail, healthcare, and more.
We built a docs site that references code samples from external files to avoid copy-paste errors, makes it easier to manage code updates over time, and allows for separate testing processes to be run to validate referenced code. Here’s how.
Nextmv Cloud has a new look and new charts to help you better understand and refine your routing results.
Get an early look at a feature that would allow business users, analysts, or modelers to change output data, recompute statistics, and compare to another model run.
Feedback on any project is inevitable. With optimization projects and decision models, we're developing more efficient commenting and feedback loops that sit alongside modeling work.
Why did the model choose that plan? How much better is the optimization’s plan than mine? Nextmv is helping operators, analysts, and business users more efficiently answer these questions with new UI features that improve decision model explainability.
