A fast-growing energy company builds linear generators—machines that generate electricity from linear motion, using hydrogen, ammonia, biogas—almost any fuel.
Amazing tech. But there’s a problem.
Energy infrastructure is changing faster than policy can keep up. Power sources are becoming decentralized. Grids are growing brittle. To stay ahead, they knew they needed machine learning solutions. For that they needed an ML platform. And it needed to be theirs.
They had to own it.
They had already selected Nebari, a robust and open source data science platform. It could be deployed across major cloud platforms, and had features for role-based access, environment management, and scalability that their team needed.
But deploying Nebari on Google Cloud Platform (GCP), within their team’s constraints, introduced two massive risks:
Their team was lean by design. They weren’t trying to become another data company. They needed someone to come in, build their ML platform, and then leave them in control.
That’s why they called OpenTeams.
Scoping
Deploy
Knowledge transfer
OpenTeams scoped the work in one week, deployed Nebari in two, and supported their team for nine months—on their terms.
With OpenTeams’ help, this energy team now runs a scalable ML platform that they fully own.
The team uses Nebari to support experimentation and data workflows—without having to escalate small issues to external vendors.
They wanted AI, but they weren’t interested in becoming a data company in the process. OpenTeams support saved them months of debugging and setup, and our engineering enhancements pushed Nebari further than before to work for their specific needs.
Every software platform tries to capture you. At OpenTeams, our goal is your sovereignty. We build data systems that you cont
OpenTeams gives you everything you need to own your stack, host your models, and control your data—with none of the managerial baggage.
We call it AI Enablement as a Service.
If you’re ready to own your AI, without baggage, you need OpenTeams.
Every January, the global economic conversation moves to a small alpine town in Switzerland. Heads of state, founders, and technologists gather in Davos to debate the future. This year, beneath the familiar headlines about geopolitical tension and economic uncertainty, another theme dominated nearly every private conversation: artificial intelligence.
