Insights
Practical thinking on AI, architecture, data, and cloud engineering from the team doing the work.
Prototypes are easy. Reliable, observable AI systems that hold up under real usage require a different set of engineering disciplines.
Xunova Engineering ·
A phased modernization strategy that reduces risk while still making meaningful progress on technical debt.
Xunova Engineering ·
Before investing in analytics or AI, most organizations need to fix the fundamentals of how their data is collected and governed.
Xunova Engineering ·
Practical, low-risk changes that reduce cloud spend without compromising reliability or performance.
Xunova Engineering ·
Most vendor evaluations focus on demos. Here's how to evaluate for what happens after the contract is signed.
Xunova Engineering ·
Velocity and story points tell you very little. These are the signals we look at when assessing a codebase and a team.
Xunova Engineering ·
Reading about the approach is a good start. Applying it to your systems is what we do — see our AI, data, and engineering services.