Whether you’ve already built a decision model or are just getting started, developing your optimization project on the Nextmv platform will give you the framework, testing tools, and ease of integration required to prove the value of your decision model.
Working in Python? Stay in Python! Develop and deploy your decision model directly from your Python environment. Updates to our SDK make it even easier to operationalize custom decision models safely and quickly.
If you’re building decision models in Python, our Python SDK and decision science platform make the development process faster (and easier) so you can get your model safely into production.
When decision models power real-life operations, any sort of model performance failure is a nightmare. Learn why observability in the operations research space is often a challenge – and how to give your team more visibility into model performance with DecisionOps.
Accelerate development of your Python decision models – from completely custom models to those built using popular modeling tools – with features for testing, deploying, managing, and collaborating.
Follow this step-by-step tutorial to go from a forecasted demand to optimized routes using OR-Tools, HiGHS, and Nextmv.
Define the metrics that matter to your organization, run an acceptance test, and get easy-to-share results that guide your team down the path to production with confidence.
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Launch and run your own routing app with a library of configurable constraints to fit your use case.
Dive into sample routing and scheduling apps in the Nextmv console that are preloaded with runs and experiments. Interact with live dashboards and explore the full functionality of these decision apps.
Access your HiGHS model remotely. Deploy your model as an app to Nextmv Cloud in minutes.
See how to build, run, and deploy a custom decision model to production in a few minutes.
Whether you operate in multiple market locations or want to expand into new ones, simple scenario testing can help you make decisions about vehicle fleet size, composition, and capabilities.
Get started with Nextmv Cloud and Go to solve a vehicle routing problem and find optimized solutions for your vehicles and stops.
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What does it mean to go from manual to automated decision-making? Why make the switch? We explore this topic and show you how.
Get started with Nextmv Cloud and Python to solve a vehicle routing problem and find optimized solutions for your vehicles and stops.
Join our team for a techtalk video as they dive into the latest routing optimization features and chat about what’s coming soon to Nextmv in the decision automation space.
Get started with the Nextmv Onfleet integration in a step-by-step walkthrough for how to pull in tasks and workers via the Onfleet API, find optimized routes with Nextmv with extended features, and upload assignments back into Onfleet's platform.
Welcome to a tour of the Nextmv Cloud console! Learn how to get started with sample files for your routing use case. Optimize routes for delivery, distribution, and sourcing with Nextmv.Get started with Nextmv Cloud with our documentation.
Solve routing problems like delivery, distribution, and sourcing with Nextmv Cloud. See your optimized routes on the map in the console or use the API to connect to your data source and frontend UI. Scaling is fast and easy with Nextmv.
Solve your delivery and dispatch problems with Nextmv Cloud. See your optimized routes on the map in the console or use the API to connect to your data source and frontend UI. Scaling is fast and easy with Nextmv.
Solve your distribution and dispatch problems with Nextmv Cloud. See your optimized routes on the map in the console or use the API to connect to your data source and frontend UI. Scaling is fast and easy with Nextmv.
Solve your sourcing and dispatch problems with Nextmv Cloud. See your optimized routes on the map in the console or use the API to connect to your data source and frontend UI. Scaling is fast and easy with Nextmv.
Balance vehicle usage by using constraints on aspects of route to limit maximum distance traveled, maximum time spent on route, and/or maximum number of stop serviced.
When performing route optimization for use cases like delivery, distribution, and sourcing, the order in which the stops are serviced is critical. Learn how to use precedence to ensure your stops are visited in the correct sequence.
