About
Mission
Platforms scale by design
We scale platform expertise
Our origins
NeuroKube is built by SoKube, a Swiss consulting firm specializing in cloud-native technologies. Every day we design and run our clients’ Kubernetes platforms, and fix what breaks.
At every client, we see the same thing. A platform is a dozen or more interconnected components. The smallest problem means hunting through many systems: cluster state, configuration, telemetry, repositories, deployment history.
Once solved, integration edge cases between components aren’t always written down and stay in people’s heads. And because several tools exist for every component, no one can know them all. So requests and investigations end up with the same handful of experts.
NeuroKube is our answer to that, built on the principles we recommend to our clients. It was launched in spring 2026 by a team of seasoned engineers who have spent their entire careers in platform engineering and AI product development.
Our beliefs
- Humans in the work, not on the approval button. An agent should work alongside people as a colleague. That’s what produces the best results and leaves people more capable. A tool that quietly deskills its users costs more than it saves.
- With generative models, engineering judgement has never mattered more. Despite being genuinely powerful, a model is a component, not the architecture — handing it the whole job just moves the work onto people downstream. We use models where they earn their place, and build around them to make a stable, secure and cost-effective system.
- Governance is an integral part of what makes an AI initiative succeed. Deciding what to automate, or what agents can access, is a risk-benefit trade-off that belongs to the organization and differs for every setting and project. So we make our platform controllable, adjustable case by case.
Our vision
Kubernetes is where operational complexity surfaces first today, so that is where NeuroKube starts. It is not where it stops.
A symptom observed in the cluster may come from the underlying layers: the infrastructure (cloud quotas, disk I/O throttling), the network (routing, firewall rules, load balancers), the security controls (identities, access policies, certificates).
The same architecture applies to those layers. With specialized agents, a multi-source knowledge base, a system that consolidates experience into know-how to keep improving. And the investigation continues.
Resolve all your Kubernetes incidents in complex enterprise environments
The AI platform for Kubernetes and cloud-native stacks. It automates troubleshooting and resolution from the first signal to the verified fix—while you remain in control of every decision along the way.
