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Artificial intelligence
We build chatbots, integrate model APIs and run models on your own infrastructure — with retrieval, evaluation, access controls and training for the people using them.
Start a projectAI needs an engineering system around it.
30% of developers have little or no trust in AI-generated code — DORA, 2026. Evaluation, human review and operational ownership belong in the design from day one.
Read DORA’s research ↗The work
Designed for the conditions.
- Chatbot integration
- AI training
- Local AI (on-premise)
- LLM integration
- Retrieval augmented generation
- Embeddings and vector search
- AI APIs
- Evaluation and automation
One system, one team
From first idea to a system that runs.
One team for the database, the AI, the interface and the servers it all runs on.
Your existing systems
Your idea and goals
What we deliver
Running in production
Process
Clear steps, visible progress.
Frame the use case
Decide where a model genuinely helps the workflow.
Ground in data
Connect retrieval, permissions and business context.
Evaluate continuously
Measure answer quality before and after release.
Operate with controls
Guardrails, human review and cost visibility.
The work
What you get
- Model selection and cost analysis
- Retrieval and evaluation pipeline
- Guardrails and access controls
- Team training materials
Operating targets
Answer quality
Cost visibility
Security
Technology examples
TypeScriptExamples, not a fixed stack — chosen per project, with the team that will own it.
- TypeScript
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