Context beats model
Results depend less on the model than on what the agent knows about the project: architecture rules, conventions, test commands and examples. We build this foundation together with your teams.
Enterprise AI
AI Software Engineeringcoding agents in daily work.
Coding agents genuinely change software development — when context, guardrails and reviews are right. We introduce them so speed increases without quality and security suffering.
- Selection and introduction of coding agents
- Context engineering and project rules
- Safe use with code review and tests
- Measurable impact instead of gut feeling
Securing quality
Agent-generated code goes through the same gates as any other: review, tests, static analysis and dependency checks. Where pipelines are weak, agents expose that faster.
Data protection in the development process
For regulated environments, we assess operating models up to locally run models and define which repositories and data are even accessible.
Häufige Fragen
Answers to the questions we are asked most often about AI Software Engineering.
No. They speed up routine work, research and refactoring. Architecture, business decisions and responsibility for quality remain with the team.
Innovation from Munich.Active worldwide.
Talk to us about your cloud, DevOps and AI initiatives — no obligation, directly with our engineers.