Expertise
Technologies in their system context rather than as a wall of logos: application engineering, mobile, identity, and platform & operations.
The stack is a means, not a statement. A list of technologies does not answer whether a technical problem can be understood and solved dependably.
Each technology below therefore states what it is actually used for. The taxonomy is maintained centrally and linked to the service pages and articles.
Application engineering
Websites, business applications, interfaces and data flows – where technical requirements, domain logic and existing systems come together.
- PHP
- Server-side applications and interfaces, including this website.
- Python
- Data processing, automation and integration scripting.
- TypeScript
- Type-safe application logic in the browser and in Node tooling.
- PostgreSQL
- Relational storage with dependable consistency guarantees.
Mobile
Native applications for Android and iOS, including on-device data handling and release processes.
- Kotlin
- Android applications including on-device storage.
- Swift
- iOS applications following platform-native interaction patterns.
- Android
- Platform-specific requirements, permissions and store processes.
- iOS
- Review requirements, privacy declarations and release cycles.
- Offline-first
- Applications that remain fully usable without a network connection.
Identity & access
Authentication, authorisation and user management across systems that were never designed to interoperate.
- Keycloak
- Central authentication, realms, clients and role models.
- OpenID Connect
- Standardised sign-in for web and mobile clients.
- OAuth 2.0
- Delegated authorisation between services.
- SAML
- Integration with existing enterprise identity providers.
- LDAP
- Directory services as the system of record for users and groups.
- SCIM
- Automated provisioning and deprovisioning of user accounts.
AI engineering & applied AI
Machine learning, language processing and language models as part of a business application – not as a demonstration beside it.
- spaCy
- Language analysis and entity recognition in unstructured text.
- Natural Language Processing
- Making linguistic structure usable where fixed rules would be too rigid.
- Machine Learning
- Trainable classification where patterns cannot be enumerated exhaustively.
- OCR
- Text recognition in scans when a document carries no usable text layer.
- Large Language Models
- Semantic understanding where rules and classification reach their limits.
- Local LLM
- Running language models inside your own infrastructure, for example via Ollama or LM Studio.
Platform & operations
Runtime, operations and availability – the layer where architectural decisions show their cost first.
- Linux
- Operating system foundation for application and database services.
- Docker
- Reproducible runtime environments for development and operations.
- Kubernetes
- Orchestration where several services are operated together.
- Hochverfügbarkeit
- Failure behaviour, redundancy and operational boundaries – settled before the incident.
- Privacy by Design
- Data minimisation as an architectural decision, not a later setting.