A look at how to action a handful of best practices derived from experience and observation intended to improve decision model success.
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.
How Grubhub’s data science team uses Nextmv to accelerate model development, ship models as microservices, and build trust with business users.
Decision model development and collaboration is easier and faster when there’s a shared system of record to reference and interact with for I/O, results, and charts. Learn how to create one in Nextmv.
When Veho’s data science team wanted to evolve their route optimization with a new solver, they leveraged Nextmv’s DecisionOps platform to transition to Hexaly in a matter of weeks.
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.
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.
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.
The ops-ification of disciplines such as software development, machine learning, and security aims to increase efficiency and reduce risk. For decision science and operations research — a discipline built on efficiency — it’s no different.
A look at how one startup is supporting sustainable and resilient city design by optimizing urban delivery logistics — starting with dispatch apps designed for eco-friendly operators.
