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From the formal model to the system that runs in production.
We are a two-person engineering practice based in Madrid: a systems architect with two decades of delivery and P&L ownership, and a mathematician-engineer from Universidad Politécnica de Madrid. We design, build and operate production systems — mostly AI-assisted business platforms on Google Cloud.
This organization is not our product. It is our evidence.
Our client code is private, as it should be. What lives here is the part that is actually worth reading: the architectures we chose, the trade-offs we made, and the lessons production taught us the hard way.
| Repository | What it is |
|---|---|
| engineering-handbook | Lessons validated in production. Each one: what failed, why, the correct pattern, and how to verify it. Written after the incident, not before. |
| case-studies | Real systems we designed and operate, described by problem and architecture. Identified by sector, geography and year only — never by name. |
| reference-architectures | Diagrams and ADRs for patterns we have shipped more than once. No code — just the reasoning. |
| toolkit | Technology inventory counted from dependency manifests. |
- Open the handbook and read any three entries. That tells you whether we have operated systems or only built them.
- Open one case study in your domain. That tells you how we reason about constraints.
- To assess Gabriel's code and academic work, open his public project portfolio.
We name no client here. Our clients authorized these write-ups; we chose not to use that permission. A system is identified by its sector, its geography and its year — never by a name, a brand, a logo or a domain. We publish no client code, no credentials, and no data about anyone's users. Metrics are relative or per-unit — never a client's commercial figures.
Nothing here is copied from a private repository. It is written from scratch, in the abstract, so that the pattern is useful to you and useless to a competitor of theirs.
| Aníbal Suárez Hernández | Electronic engineer. Systems architecture, cloud cost engineering, AI governance, delivery. Has carried projects from proposal to production and owned the number at the bottom. |
| Gabriel Suárez | BSc Mathematics and Computing (UPM), MSc Advanced Mathematics (UPM). AEM, Java, Python, mathematical modelling and machine learning. Public academic and software projects. |
We work well separately and better together: one of us asks what the system costs and how it stays up, the other asks whether it is correct. Hire either.
Madrid · open to conversations
