Masterbrain Bytes

Service 02

AI software development

We develop complete applications with local model integration and automate recurring workflows. AI speeds up development; architecture and tests decide.

Local AI only becomes useful when it is part of an application: with a user interface, data connections and automatable workflows. We build such applications end to end, from the model call to the user interface, and connect AI agents through clearly defined tools, for example via MCP.

Automating workflows

Many tasks come back regularly: selecting content, updating data, passing results on to another system. We build automation that takes over such workflows reliably, and we define where people review and decide.

Two examples from our projects: the newsletter Agrar Kompakt automatically compiles an individual selection for every recipient and sends it out. The editorial RAG updates its index automatically and makes the search available to other systems and AI agents through API and MCP interfaces.

Performance is the key

Game development taught us how to get the most out of the hardware. That is exactly what local AI applications need: the model uses graphics and system memory, and the interface should still respond instantly. That is why we use native technology where it matters and love Rust for safe, fast software. We add C++, Python and .NET depending on the task and the existing system.

Developed with AI agents

We use AI agents in our own development every day, in a fixed process with a plan, small steps, independent review and sign-off by people. That gives us high speed without giving up control over quality and architecture.

Opportunities and limits

  • Where AI helps

    • Understanding unfamiliar code
    • Building prototypes and integrations
    • Preparing tests and documentation
    • Generating variants for 3D and audio

  • What needs to be checked

    • Wrong assumptions and invented interfaces
    • Unintended changes elsewhere
    • Security and licence terms
    • Maintainability, cost and quality of results

A reliable workflow

  1. Scope the task

    Small, reviewable tasks with clear acceptance criteria.

  2. Review the change

    A second, independent model reviews every step against the plan.

  3. Run the tests

    Automated tests and version control for every step.

  4. Expert sign-off

    A passing build does not replace a review by people who know the subject.

Does this fit your task?

Tell us about your use case and your data. We will get back to you personally.

info@masterbrain-bytes.com