How confident are you in your decision model parameters? How optimized are your decision model's parameters? Learn how to systematically sweep and test and auto-select the best result per request.
Follow us on LinkedIn and subscribe to our LinkedIn newsletter.
Find the optimal mix of competing products using predictive and prescriptive analytics in a Gurobi notebook. Go from prototype to production using Nextmv to run your models remotely, create optimization pipelines, perform scenario tests, and render custom visualizations.
Track external runs of your decision model with Nextmv for instant bookkeeping and smarter collaboration.
Learn how to leverage DecisionOps to get your OR-Tools model into production faster. Then create decision workflows to automate steps in optimization pipelines, render custom visualizations, and more.
Using a Hexaly model, see how to use Nextmv ensemble definitions to automatically select the best plan from many solutions based on your specified criteria.
Deploy and run a Statsmodels ML regressor, Gurobipy price avocado optimizer, and end-to-end decision workflow on Nextmv via a Jupyter Notebook on Google Colab. Plus, visualize results using Plotly and perform a scenario test to determine relationship between price and profit.
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.
Interested in Hexaly to solve optimization problems? This techtalk covers how to get started with Hexaly in Nextmv, use features for scenario testing, best plan auto-selection, model management, and a Q&A with Hexaly’s CEO.
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.
In under ten minutes, we demo how to deploy and run your local Python decision model from a Jupyter Notebook as a fully featured decision app on the Nextmv platform for simpler collaboration and a smarter workflow.
Go from a local decision model to a remotely hosted decision application (with API endpoints) that you can easily share, test, and confidently promote to production. See the model-to-app workflow using a Jupyter Notebook and Nextmv in under 30 minutes.
Learn how to leverage data and AI for better operational decisions.