Begüm Yüzgülen
Full Stack Engineer
5 min read
Recovering a CMS that nobody in the building owns
5 min read
22 August 2026
Strategy and technical delivery
AI transformation for MedTech.
We combine MedTech expertise, governance and technical delivery – from AI strategy to integration with existing workflows and systems.
Move from AI ambition to governed adoption, operational workflows and connected platforms.
Where transformation gets stuck
AI cannot scale across fragmented processes, data and ownership.
We align business, IT and compliance around one transformation path—then prove it in a focused workflow.
See our approachWhat we do
We turn AI strategy into working operations.
One partner for strategy, workflow automation and digital platforms.
How it operates
Your AI. In your systems. Under your control.
We do not place your work on a shared Veren platform. The solution becomes part of your existing system environment and runs in infrastructure agreed with your IT team.
How we work in regulated environments01
Approved information
The workflow uses the company sources and versions your teams approve.
02
Existing systems
ERP, CRM, PIM, CMS, QMS and document systems remain part of the operating model.
03
Human approval
Sensitive and externally visible actions keep a named human checkpoint.
04
Traceable actions
Relevant inputs, decisions and follow-up actions are documented.
05
Replaceable providers
Models and providers can change without redefining the entire workflow.
06
Client ownership
Code, accounts and operating knowledge stay under client control.
Transformation and platform work in practice
01
Geuder AG
01A B2B customer portal and shared workspace that connects product data, AI-assisted content work and guided product experiences.
See the Geuder AG case study →B2B customer portalAI workflows
02
Tecan AG
02A discovery across teams, markets and systems, translated into a shared platform blueprint and implementation roadmap. Currently in progress.
See the Tecan AG case study →AI transformationDigital platforms
03
Episeras
03We translated a complex neurotechnology product, technical inputs and launch priorities into a clear product story and a focused digital product platform.
See the Episeras case study →Open live platform ↗Digital healthProduct platform
04
MEDNET
04A structured Product Finder that makes a large medical-component catalogue searchable and turns product discovery into a qualified inquiry.
See the MEDNET case study →Medical componentsLive
05
Flash Biolab
05A guided digital journey for a contract manufacturer, with clear capabilities, a transparent process and an interactive project check.
See the Flash Biolab case study →ManufacturingLive
From transformation to operation
Prove the strategy in one workflow.
Create evidence, standards and confidence for the wider rollout.
01Prioritise
Choose the right workflow
Select a relevant process with clear ownership and measurable value.
02Design
Define the operating model
Clarify decisions, data, exceptions and human approval.
03Connect
Connect approved systems
Bring together the trusted sources and applications the work requires.
04Scale
Run, measure and expand
Operate safely, measure the result and reuse what works.
AI Automation example
See how AI works across your workflow.
Choose a workflow. See the path from input to approved outcome.
01
- 01
Input
Email, web or phone
- 02
Operational AI
Understands the product question
- 03
Connected systems
PIMCRMBuilt around the systems you already use.
- 04
Outcome
Approved answer. The next action is logged.
Choose a workflow
01
Input
Email, web or phone
02
Operational AI
Understands the product question
03
Connected systems
PIM+CRM
Built around the systems you already use.
04
Outcome
Approved answer. The next action is logged.
Who you’ll be working with
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
Our team consists of seasoned experts with a genuine passion for technology and design — the same people you’ll work with from first call to launch.
Look into our knowledge
Our blog
Common questions
Before the first workflow.
What does AI transformation include for medical technology companies?
It covers AI strategy, use-case priorities, governance and technical delivery. The delivery can include controlled workflows, system integrations and digital platforms.
Which workflow should we start with?
Start with recurring work that has a clear owner, approved source information and an outcome the team can review. Product enquiries, service cases and document requests are common starting points.
Does the solution replace our ERP, CRM, PIM or CMS?
Usually not. We connect the systems already responsible for product data, customers, content and documents. A new platform is considered only when the existing setup cannot support the required workflow.
Where does the AI solution run?
It runs in infrastructure agreed with your IT team. It is not a shared Veren platform, and the client retains control of the relevant code, accounts and operating knowledge.
How do Regulatory, Quality and IT stay involved?
They help define approved sources, responsibilities, exceptions, review steps and records before implementation. They remain involved in review and acceptance where the workflow requires it.
How long does the first step take?
A focused discovery usually takes two to four weeks. It produces priorities, a system and information map, governance decisions and an implementation roadmap. Delivery time then depends on the selected workflow.
A practical first step
Find the right AI starting point.
Align the business case, governance and first implementation—without starting a large programme.