You cannot adopt AI through improvisation.
We train people in two days, join your projects, and ship one improvement every month — measured.
How We Work
Education
AI Kickstart
For a team that needs knowledge and insight into where AI actually helps.
A two-day workshop tailored to your industry and the tools you already use. Exercises run on your people's real tasks, not generic examples. After the workshop, you receive a report outlining concrete opportunities for how AI can improve your work.
Book an intro callProject collaboration
AI Value Sprint
For a project in preparation, while the scope is still open.
Over four weeks we talk to the people on the project, pick one opportunity, and build a working prototype on your data. At the end you get a report and a presentation with a recommendation for the next steps.
Book an intro callContinous partnership
AI Value Engine
For a company that wants progress to continue after the first success.
Each month we pick one thing together and deliver it within that same month. Between cycles we're available for questions. Every quarter, leadership gets a review of what was done.
How it's measured
- The baseline is captured before delivery, never after
- The method is self-assessment by the people doing the work
- Impact is checked again one month later
Zvonimir Križ
AI Adoption Strategist
Expert
Zvonimir leads AI adoption programs for mid-size and large companies. The work always starts with a diagnosis of real processes, then continues with training, hands-on project support, or a continous partnership.
Before founding Adriatech, he spent two decades in environments where mistakes come at a cost — 12 years in banking IT, where he led R&D, and as a Senior Agile Coach at Infobip. From that he carries one rule: technology is the easy part — people and processes decide whether AI is still in use three months later.
Why Now?
AI is advancing week by week, but real-world implementation often lags behind. We bridge that gap — with you in the lead role, delivering results weekly.
What Research Says
Of organizations have moved less than 30% of GenAI experiments into production
Source: Deloitte, 2024
Of companies move beyond the proof-of-concept phase with AI projects
Source: BCG, 2024
Of the engineering workforce will need to upskill by 2027
Source: Gartner, 2024
Of the main barriers to AI deployment are related to risks and governance
Source: Deloitte, 2024