AI development
AI that lands.
Language models can do real work today if they're integrated properly. We build AI features that run in production: securely connected, honestly evaluated and maintained like any good software.
Services
Four ways to bring AI into your business
LLM features in your apps
Assistants, summaries, intelligent search, data extraction: we integrate language models into your existing apps and portals with clean streaming, error handling and cost control.
- Copilot and assistant features in existing products
- Summarization, classification and data extraction
- Integration into iOS, Android and web apps
- Claude
- OpenAI
- Vercel AI SDK
- Streaming
AI agents & automation
Agents that work with tools: processing documents, triaging requests, executing multi-step workflows. We build agents with clear boundaries, logging and human oversight in the right places.
- Tool-calling agents for well-defined tasks
- Document and email processing
- Internal process automation with approval steps
- Agents
- Tool calling
- Workflows
Chat with your data (RAG)
Your knowledge, queryable in plain language: manuals, wikis, product data or contracts become searchable, with verifiable source citations instead of hallucinations.
- Knowledge assistants over your documents and data
- Retrieval pipelines with source citations
- Connections to existing systems (SharePoint, Confluence, databases)
- RAG
- Embeddings
- Vector search
AI strategy & workshops
Where does AI actually pay off in your business? In a use-case workshop we identify applications with measurable value, check feasibility honestly and tell you where AI is not (yet) the answer.
- Use-case workshops with your team
- Feasibility checks and build-vs-buy assessments
- Guidance on data protection and the EU AI Act
- Workshop
- Feasibility
- Enablement
Approach
From use case to pilot in weeks
AI projects rarely fail on technology; they fail on unclear goals. That's why we start small and measurable.
Use-case workshop
A compact workshop with your team: where does work pile up that a language model could take over? We prioritize by value and feasibility and define how success will be measured.
Pilot on your data
Within two to four weeks we build a working prototype using your real data and workflows. You see concretely what the model can do and what it can't.
Production & operations
A successful pilot becomes a product: integration into your systems, evaluation, monitoring, cost control and operations that keep pace with new model generations.
In practice
We ship features, not slide decks
Trial-finder assistant for TRICLI
For the patient portal studiefinden.de we built an AI assistant that guides patients to matching clinical trials in a conversation, using a tool-calling agent with a strict medical safety framework, rate limiting and abuse protection, running in production.
LLM tooling in our own stack
Our translation pipeline @venqoo/localizer translates software copy with pluggable LLM providers, OpenAI and the Claude Agent SDK, and runs in production across our own projects.
AI-assisted development
We work with agentic development tools every day and know first-hand what agents can do reliably and where they need oversight. That practice flows into every client project.
Reliability
AI your data-protection officer will approve
EU hosting on request
GDPR-compliant architectures with Azure OpenAI in EU regions and data-processing agreements.Your data stays yours
No training of third-party models on your data. We select providers and contracts accordingly.No vendor lock-in
We build model-agnostic: Claude, OpenAI or Azure OpenAI stay interchangeable as the market moves.Measured, not magical
Every AI feature gets evaluation and monitoring, so you see how well it actually performs.
FAQ
Common questions about AI projects
What does an AI project cost?
A use-case workshop is a compact fixed-price format. Pilots typically land in the lower five-figure range depending on scope, far less than a full product development cycle, because we build on existing models. After the pilot you get a reliable estimate for the production phase.
Is our data safe?
Yes, if the architecture is right. We use providers with contractual guarantees that your data won't be used for training, with EU hosting via Azure OpenAI and data-processing agreements on request. Sensitive data can be pseudonymized or filtered before it reaches the model.
Which model is the right one?
The use case decides, not the hype. Many tasks are well served by small, fast models, which keeps running costs down. We evaluate candidates against your real data and build so that switching models later isn't a rebuild.
What if it doesn't work?
Then you find out after weeks, not months. That's exactly what the pilot is for. Some use cases can't be solved reliably with today's models. We tell you that openly and suggest alternatives instead of keeping a project artificially alive.
Which task should AI take over for you?
Tell us about your use case. In a free initial consultation you'll get an honest assessment of feasibility and effort.