Problem
NPLabs needed to move from spreadsheets, calls, and fragmented coordination into a digital workflow that could support regulated pharmacy operations without creating compliance debt.
Case study
NPLabs: from fragmented operations to a live regulated platform.
NPLabs is an EU compounding pharmacy in Athens. The engagement shows how a founder-led AI and workflow operator can help a regulated business move faster without pretending regulation disappears.
This is currently the main public case study behind Arvanu. I would rather show one real project with detail than dilute the site with broad claims that a buyer cannot inspect.
Snapshot
Timeline
87 days to production
Context
EU compounding pharmacy in Athens
Catalog complexity
1,000+ medication variants
Operating model
Five user roles across the workflow
What the work involved
Constraints
The platform had to support multiple user roles, sensitive workflow data, payments inside the flow, and the kind of traceability expected in a regulated environment.
What I worked on
Architecture, workflow design, platform decisions, and AI-enabled operating features that helped move the team toward a usable production system rather than another disconnected software project.
Why this matters
This is the kind of work Arvanu is built for: practical AI inside a real operational workflow, with governance and delivery pressure in the room from the start.
Platform highlights
Role-based portals for patients, clinicians, pharmacists, operations, and admin
Workflow and data design built around GDPR and regulated pharmacy requirements from the start
Online payments integrated into the operating flow
AI-assisted treatment recommendation and workflow support inside the platform
Operational dashboards used by the team in daily work
What this proves
The first useful AI project in a regulated company is usually a workflow project, not a chatbot project.
Governance has to be designed into the process and data model, not added after launch.
A solo embedded operator can be credible when the scope is tight, the decisions are clear, and the proof is real.
Best use of this case study
Use it to judge how I think, not to pretend I am a giant firm.
The value of the NPLabs story is not “look how many logos there are.” The value is that it shows the shape of the work: workflow design, production pressure, AI features inside a business process, and operational judgment in a regulated context.