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Optimization hackathons, code fests, and innovation challenges on Nextmv

Looking to innovate in operations research? Or better translate academic research to industrial practice? Build or practice modeling skills set up for real-world impact? Check out this starter guide to hosting challenges on Nextmv.

5 things software teams should know about operations research and decision science

Decision models are sophisticated algorithms that power revenue, sustainability, and efficiency goals through optimized planning. But integrating them into software stacks is not always straightforward.

Nextmv + Python: An end-to-end decision model workflow with DecisionOps

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.

New integration: Bring your Hexaly decision model to Nextmv

Solve optimization problems with Hexaly? The Nextmv Hexaly integration provides a new way to efficiently run, test, and manage Hexaly decision models with Nextmv’s DecisionOps tools and infrastructure.

How to scale logistics planning with optimization models

What if you could explore 100s or 1,000s of possible plans in seconds instead of 10s of plans in days or weeks? Optimization models make this possible all while keeping humans in the loop to ensure quality and build trust.

Operationalizing Python decision models: configurable options, simple I/O, custom logging, and more

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.