DIGITAL ENABLER · BARCELONA

Your business deserves a real system.

4+
Active projects
100%
Cloud-native
Iterations

Simple, tailored systems to eliminate manual chaos and gain control over your business, without technological complexity.

↔️ Context scattered across teams and tools
🔗 Personal dependencies that make the system fragile
⛓️ Processes that disconnect decisions from execution
🔌 Technology that exists but never becomes useful capacity

We'll tell you in 48h if we can help and how. No strings attached.

DyMagoo is a Digital Enabler.

An enabling layer that turns operational and technological complexity into clearer, more useful and more sustainable systems.

Projects

Built in the lab

We only offer what we use ourselves and truly believe in.

01
OpenClaw
Our AI agent platform. Orchestrates autonomous agents with Spring AI, Claude API and Ollama, connecting any tool via MCP protocols.
Active
Spring BootClaude APIMCP
02
DyMagoo Engine
Our DevOps lab on OKD. The cornerstone of all infrastructure: CI/CD, Traefik, Gitea, Jenkins, Grafana and Keycloak — all integrated and running in production.
Active
OKDTraefikIaC
03
DyMagoo OS
The operating system for our AI agents. We coordinate autonomous agent teams with Linear, MongoDB and our own MCP protocols. Session by session.
Beta
AgentsLinearMCP
04
DyMagoo Web
Multilingual corporate website built with Astro and a dynamic CMS. Deployed on Cloudflare Pages. DyMagoo's story made visible.
In progress
AstroCloudflareCMS
Brand Principles

Our DNA

Eight principles that define how we think, how we build and who we build for. Rebellious thinking with purpose as the thread running through everything we do under the DyMagoo brand.

Methodology

How we
work

We have no magic formula. We have a rigorous process that we've tested, broken and improved in our own lab before applying it to your projects.

Our promise: we deliver in weeks, not months. No budget surprises. No code you won't understand. And if something doesn't work as expected, we fix it.

Technologies

Our
stack

We use technology proven in our own lab. Nothing we haven't broken, repaired and shipped to production ourselves.

Legend
Core technology — foundation of every project Complementary technology — used as needed
Journal

The process, in the open

Lab posts: real decisions, mistakes and lessons learned.

Lab #3
Building an AI lab with OKD and Ollama
Step by step: how we set up the local inference infrastructure integrated with the DevOps stack.
Lab #4
Architecture and hardware for a local AI lab
Why the Mac mini M4 Pro and the trade-offs we made between cost, performance and scalability.
Lab #5
OpenClaw: an AI agent built from the lab
How we designed the architecture of an agent with Spring AI, Claude API and Ollama on OKD.
Lab #6
AI agents in production: what we've learned
Twelve milestones and three mistakes from operating autonomous agents in a real environment. The lessons no documentation explains.
Story #1
DyMagoo: born in a lab
The story of a worker cooperative that was born building its own AI infrastructure. Because the best way to understand technology is to live it.
Story #2
DyMagoo's coordination runs on AI agents. What we've learned.
We built our own operational coordination system on autonomous AI agents. Not to experiment — out of necessity. Here's what we've learned in the first months.
Story #3
Automating without changing your tools. Where we start.
The first question SMEs ask us is: 'Will we have to change all our tools?' The short answer is: no. The long answer is here.
Story #4
Publishing without losing control. The editorial circuit we built.
At DyMagoo, web content is generated by an AI agent. But not without oversight: there are roles, states and human approval at every step. Here's the real circuit we use.
Story #5
When automation isn't enough
The AI does the work. But no one uses it. The invisible problem of adoption in automation projects.
Story #6
Why the first month is usually the hardest
And why we say so from day one. The J curve and how to prepare for change when implementing a new system.
Story #7
How we measure what has changed
Because standard KPIs don't capture everything that transforms. The two measures we use to evaluate real change in processes and people.
Story #8
The difference between delegating and trusting
It's not a technology change. It's a visibility change. How monitoring shifts from control to operational trust.
Story #9
Why we don't work for everyone
It's not exclusivity. It's coherence. Why DyMagoo is selective about the projects it takes on — and why that's a guarantee for clients who do fit.
Story #10
When clients don't know what they want until they see it
How we accompany clients who can't quite articulate what they need, and why the exploration step is half the work.
Story #11
The mistake that makes you better
How diagnostic errors, handled honestly, build real trust with the client. Because trust is built in the moments when something fails.
Story #12
When it's too soon to automate
Automating a chaotic process doesn't fix it — it leaves it chaotic at machine speed. The fifteen-minute rule as a criterion for knowing when you're truly ready to scale.
Story #13
How you know when change has truly worked
The difference between a project that has ended and a change that has truly taken root. Three signs that tell you if change is real: autonomous use, ability to repair, and self-extension.
Contact

Let's talk about
your project.

Got a cloud, AI or automation challenge? Tell us about it. We reply within 48h.

We work until they no longer need us.

Required field
Required field