01
Production-grade AI
Move from experiments to AI systems you can rely on.
- Enterprise LLM applications
- Agentic workflows
- Retrieval-augmented generation
- Private and on-premise AI
- Evaluation and guardrails
Production-grade AI & software engineering · Switzerland
We engineer software that survives contact with reality.
Production-grade AI, data platforms and custom software for organizations that need more than a prototype. We take systems from conception to production, building them for reliable operation, long-term maintainability and future extensibility.
Deep engineering expertise across AI/ML, distributed systems, cloud platforms and regulated environments.
The difference
AI is easy to demo. Building secure, observable, maintainable systems that people can depend on every day is engineering. That means thinking beyond the model: architecture, observability, security, deployment, testing, maintainability and operations from day one.
Observable
If it runs in production, it is measured, alerted on, and understood. No silent failure modes.
Secure by design
Private and on-premise options, data residency, and least privilege from the first line, not bolted on later.
Built to operate
Deployment, testing and on-call are part of the design. We stay past launch, so the system keeps delivering.
What we do
Capabilities, not a technology checklist.
Four kinds of work, one standard: it has to hold up in production.
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Data & machine learning
Turn data into operational systems, not one-off notebooks.
- Machine learning and forecasting
- Data engineering and pipelines
- MLOps and model serving
- Data platforms and warehouses
- Anomaly and drift detection
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Custom software engineering
Backends and platforms designed to last.
- Distributed and backend systems
- APIs and integrations
- Cloud-native platforms
- Performance and scaling
- Modernization of legacy systems
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Architecture & technical leadership
Reduce technical risk before it becomes technical debt.
- Solution architecture
- Technical due diligence
- Rescue of stalled projects
- Fractional engineering leadership
- AI strategy: where it pays, and where it does not
Typical engagements
The conversations that bring people here.
We want to use AI without exposing sensitive company data.
Our proof of concept needs to become a real production system.
We inherited an AI project that nobody wants to maintain.
Our architecture stopped scaling and we need a way forward.
We need senior technical leadership for a critical build.
If AI actually helps here, show us where. If not, say so.
How we work
A predictable path from objective to operation.
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Understand
Business objectives first. We agree on what success means before touching a keyboard.
02
Design
Architecture before implementation. The hard decisions are made deliberately, on paper.
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Build
Iterative delivery in working increments, with tests and review as we go.
04
Deploy
Ship to production with observability, security and rollback in place.
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Operate
We stay for the part most consultancies skip: keeping it running, and handing it over well.
Insights
Notes from the work.
Start here
The AI Discovery Workshop.
One focused engagement to find where AI is worth building in your business, and where it is not. You leave with an architecture sketch, a shortlist of opportunities, and an honest recommendation.
CHF 2,500
Fixed price · one to two weeks