How we work
AI is a tool. We set the quality of the results.
AI multiplies expertise; it does not replace analysis and decomposition. The layers make sure AI gets the right context and a task of the right size. That is why the results hold their quality.
When a prompt is enough
Two situations, two approaches
A prompt is enough
- An isolated, well-bounded task.
- A clear brief and a verifiable result.
- Low risk if it goes wrong.
Example: A utility, a data transformation, a prototype.
We use AI to the full. It is faster than a person and a mistake shows immediately.
Decomposition first
- Changes to integrations, legacy code or production data.
- An ambiguous brief where the goal is still being found.
- Regulatory, security or financial impact.
Example: A change across systems, a migration, live data.
First break it into parts, then AI on each one with full context. Faster and safer than one big prompt.
What the client gets
Security, quality and speed. In that order.
- 1
Security
- Sensitive data on our infrastructure.
- Clear rules for public tools.
- An auditable chain end to end.
- 2
Quality
- AI review on every code change.
- Answers grounded in documentation.
- Two-stage review: AI and a senior.
- 3
Speed
- Routine automated.
- Faster implementation of well-specified tasks.
- Shorter onboarding thanks to accessible knowledge.
Roadmap
Where we are taking it
Concrete directions, not a vision. Some we are piloting, some we are proposing, and we want to set the priority with clients.
Knowledge assistant over projects
RAG over the documentation of a client’s systems: one source of truth for development, operations and the client.
Automated test generation
AI proposes and maintains tests. Higher coverage without more effort.
Design and code via Penpot
Two-way connection of design and code as a standard workflow.
AI in incident response
Log analysis, event correlation and a first diagnosis within minutes.
Agentic operations workflows
n8n and a language model: triage, briefing material and routine steps with human approval.
Evaluating AI quality
We measure where AI helps and where it does not, and deploy it accordingly.
No-obligation consultation
Let’s find the first job for AI in your company.
An hour’s conversation about where your data lives, which processes slow you down and what of it may leave your network. You leave with a proposal for a first pilot, not a tool demo.
Built and is accountable for the AI layer at Nux
Radek Růžička
Managing Director and CTO, Nux s.r.o.