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They Didn’t Want a Vendor. They Wanted Ownership.
How One Energy Company Escaped AI Lock-In—And Took Control
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.
The Problem
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:
- No backup protocol
- No support channels
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.
The OpenTeams Solution
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.
| Challenge | OpenTeams Solution |
|---|---|
| No robust AI/ML platform | GCP-native Nebari install, preconfigured |
| No internal DevOps expert | DevOps-free platform management tools |
| No backup + restore options | Feature added to Nebari + tested for GCP |
| No support overhead wanted | Scoped ticket system only for actual issues |
| No vendor lock-in | Open source platform + Full doc handoff + internal Capability uplift |
This energy team got exactly what they needed, and nothing they didn’t. And when OpenTeams stepped back, they inherited infrastructure they understood.
What Changed
With OpenTeams’ help, this energy team now runs a scalable ML platform that they fully own.
- Reduced recovery time by automating critical system backups.
- Eliminated hidden dependencies, making internal audits easier.
- Improved long-term sustainability, since no proprietary software limits their roadmap.
The team uses Nebari to support experimentation and data workflows—without having to escalate small issues to external vendors.
Why It Worked
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 control.
The Difference Between a Vendor and a Partner
| Traditional Vendor | OpenTeams | |
|---|---|---|
| Stack Ownership | They own the roadmap | You own it |
| Support Model | Monthly fees, slow escalations | Scoped to your needs, ticket-based |
| Handoff | Retained control, unclear docs | Clean docs + working knowledge |
| Lock-in Risk | High | Zero |
Bottom Line
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.
Build the AI you actually own.
Talk to the engineers behind the open-source foundations of modern AI about scoping your owned-intelligence roadmap.
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