Ryan O'Neil

Co-Founder & CTO
Ryan O'Neil led the Decision Engineering department at Grubhub and Zoomer, which owned forecasting, scheduling, routing, and simulation. Ryan worked as an Operations Research Analyst at MITRE, and led software teams at The Washington Post, Yhat, and Polimetrix. During this, he earned a PhD in Operations Research at George Mason University, and wrote his dissertation on real time routing for pickup and delivery problems.‍
Nextmv Gurobi integration: Build, test, deploy decision models using Gurobi and DecisionOps

Do you solve decision science problems with Gurobi? The Nextmv Gurobi integration accelerates how you run, test, and deploy decision models running Gurobi with Nexmv’s DecisionOps platform.

CI/CD for decision science: What is it, how does it work, and why does it matter?

CI/CD is how you ship higher quality code to production faster. But with decision science models, there’s a twist. We’ll look at the role of decision quality, specific testing tooling, and problem drift on CI/CD for decision science models.

New decision apps, an open source decision model hub, and an individual plan

Many awesome projects and people underpin the optimization world. We're making mvs to surface more open source model code for real-world impact and better support individual decision modelers.

Shift scheduling optimization: Generating shift types, planning for demand, and assigning workers

Solving a workforce scheduling problem? Not sure where to start? We walk through the basics and cover what you need to know about optimizing and automating shift scheduling.

You need a solver. What is a solver?

Solvers are a source of an invisible kind of magic. When they’re absent, we notice. So what are they, how do you use one, and why do you need one?

Getting started with DecisionOps for decision science models using Gurobi

Learn how to accelerate development of decision models that use Gurobi with tools for historical and online testing, run history, model management, and model collaboration.

Forecast, schedule, route: 3 starter models for on-demand logistics

Automating on-demand logistics operations for scale, customization, and iteration is easier than you might think. Learn how to build, test, and deploy models for demand forecasting, shift scheduling, and route creation.

Several people are optimizing: Collaborative workflows for decision model operations

The next era of optimization isn't about building a better solver. It's about collaborative, opinionated tooling that empowers teams to move faster with less confusion and more access to the decision technology ecosystem.

Decision diagrams in operations research, optimization, vehicle routing, and beyond

In the beginning there was linear programming. It spawned decades of similarly-shaped solver offshoots. Decision diagrams break with this classic paradigm and offer new opportunities to solve common optimization problems.

In conversation with Dr. Karla Hoffman about optimization and operations research

Is optimization a solved problem? How does it fit into modern business models such as on-demand delivery? What does it mean to model like an operator? We’ll ask Dr. Hoffman these questions and more.

Decision model, meet production

Nextmv is removing the roadblocks for going from optimization problem definition to production environment. This makes optimization easier for operations researchers and more accessible to developers. See what this looks like and watch a demo.