A look at how to action a handful of best practices derived from experience and observation intended to improve decision model success.
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Simplify the collaboration between model developers and end users with DecisionOps. Compare runs, perform scenario tests, create shadow model versions, and share the results with a click.
We’re joining forces with FICO to unlock a new level of DecisionOps and agentic AI decision workflows that will boost decision model governance, observability, and reliability.
The path to production is a journey that necessitates applying software engineering practices to mathematical modeling. Learn about ways to demystify and streamline that process in this panel discussion.
What does agility look like in the decision science space? Learn about the factors that accelerate decision model development and prototyping, ensure quality, and deliver project value.
Learn how to automate quality check workflows for decision apps using Nextmv’s acceptance testing, model management, and Git platform of your choice.
Behind every optimization project, there’s a compelling origin story to be told. Learn about tough (and valuable!) lessons in practicing OR from the folks who’ve lived them.
We walk through the Nextmv MCP Server's functionality for interacting with Nextmv decision apps via AI agents in a safe, consistent, and reliable way.
How are open source projects being used today? How should the community think about adoption and participation? Hear from members of the Pyomo and HiGHS teams.
A simple one-line command unlocks everything you need for seamless DecisionOps-powered model development from your local machine to remote infra for testing and production runs.
An overview of approaches for managing model versions for testing, roll out, roll back, and provisioning by geographic region, client, or development environment in the context of DecisionOps.
Human review and feedback is part of any good decision workflow. Learn what decision algorithm developers and teams can do to increase trust and build confidence.
The future of operations research and decision science hinges on DecisionOps infrastructure, systems of record, and an integrated ecosystem.