The work we've done
Real engagements, described by the capability behind them, not the logo on the door.
Our work page shows the shape of the problems we solve, not the logos we solve them for. Each case study is abstracted on purpose: the domain, the architecture decision, the constraint, and the outcome stay; the client name does not. We pick examples that teach you something about how we think under real pressure, so you can judge whether nuvio is the right partner for the system you are trying to build.
How we choose what to show
We select work for what it demonstrates, not for how impressive the name sounds. A good case study isolates one hard decision -- a data model that had to survive a 10x increase, a migration that could not take the product offline, an LLM feature that needed to be trustworthy before it was clever -- and shows the reasoning that got us there. We favor examples where the constraint was sharp and the trade-off was real, because those reveal judgment. We deliberately leave out work that went well only because nothing went wrong; it teaches you nothing about how we behave when something does. The goal is that you finish reading and understand how we'd approach your problem, not just that we've been busy.
Why client names are withheld
We don't name clients because the people who hire us value discretion, and because a logo proves almost nothing about the work. Knowing that a recognizable company worked with someone tells you that company had a budget, not that the engineering was sound. We'd rather show you the actual architecture decision and let you evaluate it on its merits. This also keeps us honest: when we can't lean on a famous name, the case study has to stand on the quality of the thinking. If you need references during an engagement conversation, we arrange them privately, with the client's consent. On the public surface, the work speaks; the names stay out of it.
What a case study demonstrates
Each case study is built to answer one question: how does nuvio work when the problem is genuinely hard? So we write them around the decision, not the deliverable. You'll see the constraint we started with, the options we weighed, why we ruled the wrong ones out, and what the system looked like afterward. We include the parts that are usually edited out -- where the first approach failed, what we changed, what we'd do differently now. That's the signal a technical buyer actually needs. A polished outcome with no reasoning behind it is marketing; a clear chain of decisions is evidence. We aim for evidence.