The engineering team for AI transformation in medical technology.
We build the workflows and digital platforms behind AI transformation in medical technology.
We build the solutions companies keep — the platform still running in five years, still being extended, still maintained by the team who owns it.
Two founders who kept meeting the same problem
Veren started because we kept being brought into projects at the point where they were already in trouble. A digital presence that had quietly become a platform. A product catalogue maintained in three systems that disagreed with each other. A launch date that assumed the integration work was a detail.
The pattern was always the same: the technical decisions that mattered most had been made early, by people who were not going to live with them. So we built a firm around being in the room for those decisions — and around still being there two years later, when they are load-bearing.
That shapes what we take on. Senior people stay close to every engagement, especially in sectors where getting it wrong is expensive: medical technology, life sciences and research-driven organizations. It is how we keep decisions clear and the work accountable.
Four things we hold to.
Not values on a wall — the working rules that decide what we say yes to and how a project runs once it starts.
The people you meet are the people who build it
No handover from a sales team to a delivery team you have not met. The engineers in the first call are the engineers writing the code.
We say what we think before you commit
If a brief is scoped wrong, if the content model will not carry what you are planning, if a deadline assumes work nobody has costed — you hear it early, when it is still cheap to change.
Structure before features
How the data is modelled and which system owns which field decides everything that comes after. We spend real time there before anyone designs a screen.
Built to be handed over
Your team should be able to run the thing without us. Documentation, a content model people understand, and no cleverness that only its author can maintain.
Who you’ll actually work with.
Eleven people, four of them AI engineers. You work directly with the people building your solution.
Merdan Özdogan
Chief Executive Officer
Strategy, UX, project leadership
Victor Daj
Chief Technical Officer
Architecture, development, technical leadership
Begüm Yüzgülen
Full Stack Engineer
Product features, APIs, frontend and backend
Ievgeniia Dubrovska
SEO & GEO Expert
Search strategy, AI visibility, content intelligence
Ionut Burghel
Principal AI Engineer
APIs, infrastructure, systems architecture
Samuel Niguleasa
AI Native Engineer
Agent tooling, prototyping, applied AI
Denis Sorescu
AI Native Engineer
AI-assisted development, prototyping, automation
Silviu Vijiala
Senior AI Native Engineer
AI architecture, agent systems, integrations
Paul Bucea
Senior Project Manager
Delivery, planning, client communication
Bogdan Monea
Frontend Architect & Design Systems
Interface architecture, design systems, performance
Jose Rodriguez
DevOps Architect & Integrations
Infrastructure, deployment, third-party integrations
Most people overestimate what they can do in one year and underestimate what they can do in ten years.Bill Gates
Fewer surprises, earlier.
Most of what goes wrong in a platform project is decided in the first month. So that is where we put the effort.
We start with the systems you already have
What runs today, who maintains it, which system owns which field. Usually the honest answer is “more than one”, and that is the first thing to settle.
We scope against the business, not the brief
If the brief and the business are asking for different things, we say so before the estimate — with what we would do instead.
We build in the open
Working software you can click through early and often, not a reveal at the end. Changing your mind is cheap while it is still a branch.
We stay past launch
The interesting work is what happens after go-live: the next market, the next product line, the next integration. That is where a platform earns back what it cost.
Tell us what you’re building.
A first call is a conversation about your systems and what is in the way — not a pitch.
Find the right AI starting point.
Align the business case, governance and first implementation—without starting a large programme.