How Grubhub’s data science team uses Nextmv to accelerate model development, ship models as microservices, and build trust with business users.

How can GPUs improve decision optimization workflows? In what ways will solving optimization problems change? How does this change the way technology leaders think about their AI strategies? We spoke with the NVIDIA cuOpt team to find out.

Advice and perspectives from Ryan O’Neil and Thiago Serra about moving from academic settings and research environments to industry practice.

Explore customizable GAMS decision models using starter applications on Nextmv, a collaborative DecisionOps platform for streamlined testing, deployment, and management. Run your GAMS decision apps remotely with an API, answer what-if questions, and easily access run input and logs.

Pair Verso’s real-time, Vroom-based routing SaaS with Nextmv for visualizing routes on a map, creating a system of record for the routing app, performing tests, and collaborating with teammates.

Introducing a free, open source framework for more efficient decision model development: Track model runs, easily find input and output, manage visual assets, and more with the local Nextmv experience.

Say 👋 hello to Nextmv support for NVIDIA’s cuOpt optimization engine and NVIDIA GPU-enabled compute on the Nextmv DecisionOps platform. 

Tune into DecisionFest to hear from industry practitioners from organizations such as IKEA, Walmart, Carvana, Toyota, and more!

Developing, testing, or managing Pyomo models? Connect your Pyomo model to the Nextmv platform for streamlined development, simple deployment, built-in testing, and collaboration.

Explore the applications of mathematical optimization alongside the AI/ML landscape for predictive analytics, LLMs, and beyond.

Record your assignment model runs, results, input data, and more in Nextmv. Add a few lines of code to your existing model to track every run and easily share data with your teammates.

This interview explores perspectives on the intersection of ML and OR, challenges and opportunities for data scientists in the optimization space, observations in industry, and why now is a great time for practitioners to expand their skillset.