More and more of our daily lives rely on logistics automation.
Just think about it, you may have ordered Grubhub for dinner last night, Instacart for your groceries, or Takl for your home repair. In all of these cases, your experience is determined by an algorithm (often many!).
These may seem like simple systems. Just assign the closest driver to the next delivery, right? Wrong. These decision models take in tons of information to make sure not only you have a good experience but all the other users do too. If you listen to tech news, you know that margins in logistics are really low and automation is core to these on demand platforms as they scale.
That’s why we created Hop, to help you build algorithms the same way you build other software - with simple, interpretable computer code.
Hop is a decision modeling and optimization tool built for developers. It helps you automate decisions like routing, scheduling, and assignment.
Hop helps you put automated decisions in place quickly, iterate on them easily as your requirements change, and automatically gather evidence along the way so you know if it's working the way you want. This minimizes time spent on infrastructure and maximizes your impact as a modeler.
Hop is unique in that it encourages users to follow decision engineering best practices. An automated decision should be:
Repeatable decisions are easy to create and deploy to different environments. They are configured the same way in research and development, testing, and deployment. They can re-use business logic so you don't violate the DRY principle (don't repeat yourself).
Testable models are easy to validate and configure in CI/CD. Recoding decision logic into an unfamiliar language (e.g. linear inequality systems) introduces layers of potential errors. Hop models are built from state. This makes testing decisions like testing other software.
Interpretable decisions don't require complex data transformation once a decision is made. Decisions can be stored and queried directly just like any other data. They can be picked up and re-created from their inputs for debugging. The modeler owns the model. It's not a black box behind a REST API.
We help you get automated systems off the ground fast and support with experimentation tools like simulation to demonstrate performance. This lets you speak the same language as your stakeholders - KPIs and profitability.
We launched Hop in December and our first user developed an optimization algorithm for minimizing delivery time in less than 24 hours.
We’re nextmv and we help you build algorithms in days vs months.
You have two vehicles and ten locations to visit. What's the best way to route your fleet? You have seconds to solve and Nextmv Cloud. Ready, set, go!
Transporting raw milk from farms to processing plants is a daily occurrence that seems simple at first glance. But it gets complex quickly when time is of the essence and milk volumes vary.
We've released Hop v0.7.0! This release introduces a cool new feature we call expanders into Hop to help customers manage time to first feasible solution and memory use as they scale their models.
Building decision models into binaries is a beautiful thing. It eliminates a lot of sticky deployment processes and gets you to production faster.
We're thrilled to have FirstMark Capital lead our Series A round, putting even more momentum behind our vision to bring the power of decision science to every developer.
Everyone talks about Santa's big night on his sleigh - a vision of efficiency with millions of chimneys traversed in a mere 24 hours
Launching Nextmv Cloud
Our quarantined world is even more on-demand than it used to be. We order groceries, gadgets and green goddess salad, and they all show up at our doors within minutes.
Routing, Packing, and Clustering - Optimization Fundamentals
We completed our seed round!
How does Hop make decisions?
What does nextmv do?