Blog

In conversation about DecisionOps with Fred Gardi, founder and CEO of Hexaly

This interview explores perspectives on growth and adoption of optimization across practitioners, challenges and opportunities in the optimization space, thinking about optimization in broader AI strategies, and DecisionOps + Hexaly.

Replay optimization model runs under different conditions with scenario testing

Identify better plans by replaying your run with varying settings. Create multiple scenarios to understand the impact of input data, model configuration, and more on your KPIs in Nextmv’s UI.

MatchBack Systems: Eliminating historical drayage inefficiencies for imports and exports

Optimization plays a key role in MatchBack Systems successfully minimizing costs and improving equipment utilization for its customers — but it's the speed to deployment and model iteration that takes their solution to the next level.

Render custom visualizations for your optimization model with Plotly, Chart.js, and GeoJSON

Standardize and manage custom visuals as data assets in Nextmv alongside your model. Accelerate your workflows with interactive charts, plots, and maps that automatically render alongside run details for streamlined analysis and collaboration.

Reproduce and replay optimization model runs to troubleshoot operational issues faster

When an operational issue is reported, reproducing it is one of the first steps in an investigation. Finding and connecting the data you need to triage the issue can be intensive. With Nextmv, replaying history (with easy access to all the data) is just a click away.

Deploy Python decision models as hosted apps directly from a Jupyter Notebook

Push your Python decision model from a local file to a remote application in minutes – whether you’re using a notebook or running in another Python environment. Conduct tests with fully featured experimentation tooling, collaborate and share results with teammates, and get observability into model performance.