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Independent engineering practice

Intelligence.Built intothe system.

Designing software systems, AI integrations and business process automation.

Discuss a projectOur approach
[02]

Expertise

02 / 06

Three disciplines,
one engineering practice.

  1. 02.1

    AI Engineering

    Designing and integrating intelligent systems.

    In the system: the cross-cutting AI layer

  2. 02.2

    Business Automation

    Automating business processes and connecting corporate services.

    In the system: processes and integrations

  3. 02.3

    Software Engineering

    Building software systems, APIs and application architecture.

    In the system: the architecture as a whole

[03]

Approach

03 / 06
  1. 01

    Analysis

    Processes, data and constraints are studied, and the problem is stated in engineering terms.

  2. 02

    Architecture

    System structure, interfaces and integration points — before the first line of code.

  3. 03

    Build

    Development in short iterations, with readable code and documentation.

  4. 04

    Verification

    Testing, evaluation of model behaviour and risk review before launch.

  5. 05

    Evolution

    Support, monitoring and development of the system as the business changes.

    Back to stage 01

Every stage ends in a result that can be verified.

So the work can be paused, reviewed or continued without losing clarity.

[04]

Selected work

04 / 06
04.1

WayNet

Discipline
Software Engineering
Domain
VPN service
Scope
Frontend, backend, APIs, subscription system, infrastructure

Design and development of a VPN service — from the client interface to backend logic, APIs, the subscription system and infrastructure.

  1. N01Frontend
  2. N02API
  3. N03Backend
  4. N04Subscriptions
N05Infrastructure
Fig. 2 — WayNet system composition
[05]

Principles

05 / 06
  1. 05.1

    Clarity over complexity.

    Every unnecessary layer of abstraction is a future cost. We choose the simplest design that holds up under real conditions.

  2. 05.2

    Systems built to be maintained.

    Code, documentation and architecture are made to last for years — including in the hands of other engineers.

  3. 05.3

    AI where it earns its place.

    A model becomes part of a process when it solves a specific problem better than deterministic code. Otherwise, it doesn’t.

  4. 05.4

    Reliable, with people in control.

    Critical decisions stay with people. The system explains its actions, keeps a record and allows intervention.

[06]

Contact

06 / 06

Let’s discussyour project.

Open to conversations about engineering projects and AI integration — from an early idea to evolving a system that is already running.