AI/ML 
Software Development 
AI Training Programs
Hands-on workshops for development teams. Real results from the very first line of code.
AI training is a program designed for technical teams who want to consciously implement modern artificial intelligence tools in their daily work. The workshops are based on real-world scenarios and participants’ code — demonstrating how solutions like GitHub Copilot, GitLab Duo, Cursor, Tabnine, or Amazon CodeWhisperer can significantly boost efficiency in software development and documentation.
Why do AI training programs make sense?
Development teams face repetitive tasks daily — writing unit tests, updating documentation, or refactoring code. While these are essential for project quality, time pressure often pushes them aside or results in rushed execution.
Our workshops demonstrate that AI is not a futuristic add-on, but a practical tool for automating precisely these time-consuming tasks. With tools like GitHub Copilot and alternatives such as GitLab Duo, Cursor, Tabnine, and others, developers can focus on business logic and system architecture — not repetitive lines of code.
This is not a theoretical course, but hands-on collaboration using your team’s actual code — delivering immediate business value.
What challenges do technology companies bring to us?
Lack of time for writing tests and documentation
Diese Aufgaben sind zwar unerlässlich, werden aber häufig ans Projektende verschoben oder ganz ausgelassen.
Lack of knowledge about practical applications of AI in programming
Many teams have heard of AI tools, but don’t know how to use them effectively.
The need for faster onboarding of new employees
Teams are looking for ways to boost developer autonomy from the very first days on the job.
High project pressure
Every efficiency gain can translate into faster MVP delivery or reduced iteration costs.
How does our technology solve this?
We work directly with the client’s code, making it clear where and how AI can support daily tasks.
Participants not only learn how to use the tools, but also gain confidence in applying AI safely and effectively in their daily work.
Participants learn how AI tools like Copilot generate unit tests and documentation, reducing the time spent on these tasks by dozens of percent.
Minimal theory — maximum hands-on practice and ready-to-use scenarios deployable as early as the next working day.
We demonstrate how artificial intelligence can suggest improvements to existing code, ensuring project quality and readability.
We help identify the next steps — from implementing AI tools to building your own code assistants or developer agents.
Metodology 4D
Discovery
Understanding the DNA of the problem before the first line of code is written
The Discovery phase allows for a deep understanding of the business challenge, user needs, and technological context. As a result, the project starts on solid foundations, and key assumptions are validated before development begins.
Key artifact
Standardized Concept Document
Our focus
Our activities
We analyze the client’s business and technological environment: from existing systems to user needs and strategic goals. We validate business assumptions, identify risks, and define the problem to be solved. The outcome is a coherent product concept that forms the foundation for the next stages of the project.
Definition
Translating knowledge and ideas into a concrete product plan
In the Definition phase, we transform insights from Discovery into a detailed solution design. This includes defining requirements, system architecture, and the user experience concept.
Key artifact
Product & Architecture Blueprint
Our focus
Our activities
We translate business goals into specific functional and technical requirements. We design UX prototypes, define the architecture, and plan the project implementation. This ensures development starts with a clear plan and minimal risk.
Delivery
Building and delivering reliable software
In the Delivery phase, we develop the final solution. We focus on code quality, clear communication with stakeholders, and a stable product release.
Key artifact
Production-ready product / deployment
Our focus
Our activities
Our teams build the solution using modern development practices and continuous integration. We regularly test the product and maintain transparent communication with stakeholders to deliver a stable, production-ready solution.
Direction
Transforming a product into a growing digital business
Direction is a phase of long-term product development. Instead of ending cooperation after implementation, we support clients in scaling solutions, introducing innovations, and building a competitive advantage.
Key artifact
Product development and innovation roadmap
Our focus
Our activities
Together with the client, we analyze product data, identify new growth opportunities, and plan future functionalities. We help scale the solution, optimize its performance, and build a long-term product strategy.
Why train with us in AI?
- Immediate time savings — tasks that used to take hours now take minutes.
- Improved code and project quality — AI supports documentation, testing, and refactoring in real time.
- Better team morale — developers freed from routine tasks can focus on the creative aspects of their work.
- Accelerated AI adoption across the organization — the team understands how to use tools in line with IT policies and real business needs.
- Scalable knowledge — training is just the beginning — we help expand AI capabilities across the entire organization.
Where do AI workshops work best?
Document processing with artificial intelligence works best in:
Technology companies and software houses — aiming to implement AI into development processes in a conscious and practical way.
R&D and IT teams in corporations — where AI can accelerate iterations, improve documentation, and increase project predictability.
Organizations implementing DevOps or CI/CD — where automation is already standard, and AI can add another layer of optimization.
Regulated industries (e.g. critical infrastructure) — where every line of code must meet strict procedures, and AI helps maintain quality and compliance.
Startups and scale-ups — looking to grow fast without burdening teams with additional repetitive tasks.
