Outcomes before technology
We start with the process and its current burden, rather than the model. Technology serves the outcome; the measure of success is what matters.
We experienced failed AI projects ourselves before understanding why they fail. That shapes how we work today: companies rarely fail because of the technology itself, but because of the gap between an idea and reliable use. Closing that gap is our work.
We start with the process and its current burden, rather than the model. Technology serves the outcome; the measure of success is what matters.
If an AI workflow is not worthwhile, we say so. A well-founded decision not to proceed is a better outcome than a pilot that leads nowhere.
People decide at defined checkpoints. A person approves anything sent externally or made binding.
Every project ends with documentation, training and internal ownership. We remain available without making ourselves indispensable.

A business informatics specialist with more than eight years of experience spanning strategy and implementation, from enterprise architecture at Capgemini Invent to production AI systems in EnBW’s venture studio. Helps companies select AI workflows and use them with measurable results.

Azize Himtas leads enablement and rollout at EVORI, helping teams understand, control and use new workflows in their day-to-day work.
Bring a real process. An initial conversation will quickly show whether our way of working fits your needs.