
Our Tech Stack
AI-Powered Engineering
AI-assisted software development is not a hype topic for us — it is part of our daily work. We use agentic coding tools wherever they deliver measurable value: in day-to-day implementation, refactoring, code reviews and maintenance of existing systems. Our engineers stay in full control — AI is a tool that lets them work faster and more precisely, not a replacement for architecture and product decisions.
At the centre of our AI stack is Claude Code. It is deeply integrated into our development environment, knows our code conventions through project-wide instructions and executes tasks end-to-end — from requirements analysis through implementation to the merge request. Pull-request reviews, test generation and documentation are now largely AI-assisted.
We deliberately use multiple models and providers. Different strengths — different tools. Just as we choose the right tool for languages, frameworks and infrastructure, we consciously combine Claude, Gemini and other LLMs depending on the task and context.
Claude Code
Claude Code by Anthropic is a core part of our engineering workflow. We develop, refactor and review code with the CLI directly in our terminal environment — from small bug fixes to multi-file refactors. It saves time, raises code quality and gives our engineers more headroom for architecture and product decisions.
Gemini
We use Google Gemini complementarily for research, long-context analysis and multimodal tasks. Different models for different strengths — we combine deliberately rather than relying on a single tool.
Conception
Product Owner
Our greatest asset is people. Our Product Owners sit down with the client, listen, ask the right questions and translate business requirements into concrete product decisions. Before a single line of code is written, it is clear which problem we are solving for whom.
Miro
We gather ideas and requirements together in Miro. Customer-journey mapping, architecture sketches, story maps — distributed teams and clients work on the same board without insights disappearing when whiteboards are wiped.
Figma
As soon as the direction is set, we move quickly into Figma. Prototypes, clickable flows and visual designs are created early — so clients and stakeholders can experience ideas rather than just imagining them.
Languages & Frameworks
Kotlin
Kotlin is our language for backend development. Our roots are in the Java world — everything stays on the JVM, but with modern syntax, null-safety and far less boilerplate.
Arrow
We are moving from OOP towards functional programming. Arrow is the library for typed functional programming in Kotlin — it makes our domain logic more expressive and more resilient to errors.
TypeScript
In the frontend we bring designs to life with JavaScript — TypeScript only. Static types give us confidence when refactoring and make our code readable across the whole team.
Rust
Where quality and safety matter most, we write services in Rust. Errors surface at compile time — and once a service is running, it runs reliably.
Vue.js
For our frontend applications we rely on Vue 3. Why not React or Angular? Because it gets us to results quickly and produces clean, maintainable code.
Nuxt
On top of Vue we use Nuxt — the framework that gives us server-side rendering, sensible defaults and a productive developer experience, cleanly structured, SEO-friendly and fast.
Platform & Operations
AWS & Google Cloud
We run the majority of our infrastructure as Kubernetes clusters in the Amazon Cloud (set up via kops). Plan-B and failover tests run in parallel on Google Cloud — we know how to orchestrate workloads across hyperscalers robustly and cost-consciously.
Cloud (EU)
Data protection and EU sovereignty are central for many of our clients. We can also operate your workloads with European providers whose data centres are exclusively within the EU — GDPR-compliant, no third-country transfer and with clear legal frameworks.
On-Premise
We can also handle bare metal. For many companies it remains important to keep their data and servers in-house — we help operate on-premise infrastructure securely, maintainably and scalably.
Kubernetes
Kubernetes is the heart of our infrastructure. Our workloads scale automatically with load, self-healing catches failures — and our teams can focus on the application rather than the operations layer.

containerd
Our Kubernetes clusters run on containerd as the container runtime. Lean, stable and an established industry standard — exactly what we want from the layer directly beneath our services.
GitLab
Our code lives under Git version control in GitLab. CI/CD pipelines build, test and deploy our software multiple times a day — pipeline-as-code and continuous deployment are everyday practice for us, not special cases.
ArgoCD
GitOps deployments with ArgoCD: cluster state is declared and synchronised from Git. Rollouts are traceable, rollbacks are a single click, and the source of truth lives where it belongs — in the repository.
Artifactory
Release builds, Docker images and third-party libraries are all stored centrally in JFrog Artifactory. This keeps our deployments reproducible — and every dependency under control.
DataDog
Monitoring, tracing and performance analysis all converge in DataDog. Logs, metrics and traces from every service land in one place — so we find problems before our clients notice them.
Databases & Messaging
MongoDB
MongoDB databases are at the heart of our applications. A document-oriented NoSQL database fits many of our domains better than a classic relational schema — and scales with them.
Redis
We accelerate our web applications with Redis as an in-memory cache. Hot data responds in milliseconds rather than being read from the database every time.
RabbitMQ
Our services communicate asynchronously via RabbitMQ. The messaging broker reliably decouples our components and makes our architecture resilient to traffic spikes.
Complex platform. Clear ownership.
Whether it's platform modernisation, scaling or new digital products – let's look at your technical challenge together.
- ✓Experience with complex platforms
- ✓Long-term teams instead of revolving resources
- ✓Security & compliance considered from the start
- ✓Modern engineering practices with AI support