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The truth is: AI cannot replace experienced engineers, and enterprise software cannot be developed using prompts alone. What it can do, however, is significantly increase productivity throughout the entire development cycle. Find out how it works in practice now!

AI IN THE DEVELOPMENT CYCLE: WHERE IT MAKES A DIFFERENCE

  • Business Model Validation
    AI makes early decisions smarter. It can analyze markets, customer segments, and competitor offerings in minutes, giving us a strong foundation for further analysis. This accelerates validation and helps reduce costly missteps before development even begins.

  • DeIdeation & Workshop
    With tools like Miro, AI acts as a facilitator by summarizing discussions, clustering ideas, and highlighting overlooked aspects. It can instantly generate a Business Model Canvas or a SWOT analysis, ensuring workshops stay productive and no insight gets lost.

  • Rapid prototyping
    Ideas are only as good as their execution. With AI, we transform concepts into working models in days instead of weeks. It generates mockups, explores design variations, and simulates user flows. This enables smarter decisions earlier and reduces costly rework later.

  • Software Development Boost
    AI takes care of repetitive, low-value tasks such as refactoring code, generating boilerplate, and adjusting syntax. This frees our developers to focus on what really matters: understanding customer requirements and solving complex problems.

  • Testing & Quality Assurance
    Think of AI as an extra pair of eyes that never tires. It scans for bugs, inefficiencies, and vulnerabilities, while human reviewers bring judgment, context, and best practices. From generating test cases to simulating edge scenarios, AI accelerates QA while strengthening reliability.

THE ADVANTAGES IN NUMBERS

With the correct application of AI, we have achieved the following results:

  • Prototyping is possible with half the resources.
  • Many processes achieve a productivity increase of more than 20 percent.
  • Customers can innovate faster and achieve more within the same budget.

Above all, AI only delivers real results when guided by domain experts. You have probably noticed how AI sometimes makes wrong assumptions in your own field of expertise, yet feels surprisingly insightful when you explore a new area. That contrast shows why human judgment remains essential.

AI is not a replacement for high-value roles. It is an amplifier that helps experts deliver their best work more efficiently.