For my graduation internship I joined the Product Development team at AFAS Software to design and build a modular identity-verification platform in C#/.NET. Within AFAS's ERP environment, SMS and email are currently the primary methods for identity verification during onboarding, digital signing and access management, but SMS is vulnerable to SIM-swapping and phishing and isn't future-proof.

The EU is rolling out the European Digital Identity Wallet (EUDI Wallet) under eIDAS 2.0, which lets citizens and organizations identify themselves and share attributes cryptographically. The goal of my assignment is a platform that can replace or extend the current SMS/email mechanism, fits within AFAS's existing architecture, and is prepared for future integration with the EUDI Wallet.

My work spans the full lifecycle: researching the current verification process and its risks and constraints, advising on how the new platform should be set up, designing the functional and technical architecture (components, data flows, API communication, error handling, authorization and verification flows), and building a working Proof of Concept that demonstrates the technical feasibility of the design.

I'm carrying out the assignment individually, guided by my company supervisor Peter Mols, while working alongside the team responsible for the module. Generative AI tooling (such as ChatGPT or Copilot) is explicitly permitted for this assignment, in line with how AFAS itself uses AI tooling internally.

During my semester internship at ChipSoft I worked for about 5 months on the project "Meetwaardes Wearable Mobile". Within this assignment I researched, designed and built a Proof of Concept that lets medical measurements from wearables be securely shared, via the ChipSoft patient app, with the right hospital and ultimately processed into HiX, ChipSoft's electronic patient record system.

The focus was on retrieving, processing and transmitting wearable data such as heart rate, blood pressure and oxygen saturation. This required accounting for patient consent, differences between hospitals, privacy, security, data structures and possible offline scenarios. I researched Apple HealthKit and Google Health Connect, and worked out how wearable data could be normalized and mapped to a format compatible with HiX.

I also wrote a full requirements analysis: gathering requirements from stakeholders across Mobile, I&S and measurement specialists, prioritizing them with MoSCoW, and grouping them into epics such as data requests by care providers, patient consent, wearable coupling, retrieving and processing measurements, and result/history for both care providers and patients. Each epic was backed by a risk analysis with concrete, scored risks and mitigating security measures, aligned with AVG (GDPR) and NEN7510.

Based on that analysis I produced a functional and technical design and then built a working PoC with mobile functionality for patient consent and retrieving measurements, plus a backend mock demonstrating the processing and hand-off of data. I worked with C#, .NET, .NET MAUI and the ChipSoft framework. This internship gave me a lot of experience with mobile development, healthcare software, software architecture, privacy-by-design, data mapping, testing and working professionally in an R&D environment.