Was wir bauen. Was wir denken. Was die Community lernt.

Why UMH exists, how we work, and what we build.

Beyond compressed air and electricity, data should be the third resource every factory runs on. Today, it's blocked. We raised €5M to change that.

Discover why most factory-floor LLM demos break apart in production - and how a generate → freeze → test workflow instead turns "AI" into reliable, audit-grade pipelines instead of costly surprises.

A single IoT platform can tackle specific use cases but struggles with large-scale data. A Unified Namespace excels at flexible distribution yet needs extra tools. The key is striking the right balance and leveraging each where it shines

Frustrated by confusing MQTT explanations? This guide clarifies MQTT’s essentials, shows why it’s ideal for IoT telemetry, and reveals its drawbacks for manufacturing—plus how to integrate MQTT with data-center-grade solutions for end-to-end reliability.

Yes, we’ve made it possible to bring Node-RED-style simplicity into Benthos pipelines, enabling your chosen LLM to handle tedious manufacturing connectivity and contextualization tasks—whether you’re prototyping or managing production-grade data flows.

Why We Recommend Hetzner to Try Out the UMH: it is at least 4x–10x less expensive than AWS and Azure for similar VM instances.

At UMH, we’re building an integrated and user-centric solution for industrial IoT. In this article, we explore the shortcomings of typical manufacturing software and share how our unique approach addresses these challenges.

Read this article to know how modern "cloud-native" technologies such as Kubernetes, Grafana, and TimescaleDB can and must be combined with the traditional automation pyramid.