Riegel Systems

Engineering intelligent products.
From device to cloud.

Riegel Systems develops sophisticated digital products, AI systems, cloud platforms and connected devices – from electronics and embedded software to production cloud and AI systems. Across technology boundaries, from a single source.

Discuss your project Our engineering cases

Physical World → Edge → App → Cloud → Data → AI Electronics to Inference

01Capabilities

Competence across the whole stack

From electronics to AI: Riegel Systems covers four disciplines – and the interfaces between them.

AI Engineering

Produktionsfähige AI-Systeme – nicht nur Prompt-Demos.

  • Generative AI
  • LLMs
  • AI Agents
  • Multimodal AI
  • Computer Vision
  • AI Workflows

Cloud & Digital Product Engineering

Von Architektur und MVP bis zum produktiven Betrieb.

  • AWS
  • Cloud Architecture
  • Kubernetes
  • Serverless
  • SaaS
  • Web Applications

Embedded & Connected Systems

Physische Produkte mit Software, Apps, Cloud und AI verbinden.

  • Digitale Elektronik
  • Bluetooth Low Energy
  • BLE SoCs
  • Embedded Software
  • Firmware
  • Device Communication

High Performance Engineering

GPU-Anwendungen und verlustarme Datenpfade – belegt durch Voluqon.

  • C / C++
  • GPU Computing
  • Vulkan
  • CAD
  • 3D Rendering
  • WebRTC
Positioning

Senior-led. Flexibly scalable.

Riegel Systems takes on senior technical responsibility with short decision paths – and brings in experienced technology specialists when a project needs them.

How we work
02Engineering Stack

From hardware to AI

One engineering discipline across the entire product stack.

Few teams master both ends of this chain. Riegel Systems understands electronics and embedded software just as well as cloud platforms and AI systems – and takes responsibility for the connections in between: firmware, BLE, APIs, data pipelines, inference.

As a result, decisions are made across the whole stack from a single source – with system architects who can evaluate a device driver and the GPU infrastructure equally well.

  1. Electronics
  2. Embedded
  3. Connectivity
  4. Apps
  5. Cloud
  6. Processes
  7. Agents
  8. Data
  9. AI
*Proof Points

Cases in the engineering stack

Seven engineering cases cover the stack together – from electronics and embedded via apps, cloud and processes to agents and AI.

03Engineering Cases

Selected engineering cases

View all cases
In production Industrial / High Performance Engineering

Voluqon

Browser-based visualization of demanding CAD and engineering data.

Server-side processed and rendered engineering data, displayed in the browser as a high-resolution video stream with low-latency interaction.

  • C++
  • CAD Processing
  • OCCT
  • Vulkan
  • +6
In production AI-native Business Process Engineering

AI Process OS

An AI-native operating system for business processes – BPMN, natural language and a validated workflow runtime.

An AI-native operating system for business processes in which processes, capabilities, roles, events and tenants are central system elements. Natural language and BPMN yield validated, executable workflows.

  • React 19
  • TypeScript
  • Vite
  • BPMN.io
  • +9
In production Agentic Systems & MCP Engineering

Travel MCP

An MCP server for agentic price search across multiple travel portals – with hard safety boundaries.

A Model Context Protocol server that searches for package holidays across multiple portals and determines the final price before a binding action – safety first: no booking, no payment, no personal data.

  • Model Context Protocol
  • TypeScript
  • Node.js
  • Playwright
  • +5
Technology Project Embedded & Connected Systems

BlueNodes

From custom electronics and embedded firmware to a distributed BLE network and a mobile application.

A complete connected-device system: custom 4-layer PCB, embedded firmware on Nordic nRF52832, distributed BLE rebroadcasting network and a mobile control app – hardware and software from a single source.

  • Embedded Systems
  • Bluetooth Low Energy
  • BLE Mesh
  • Nordic nRF52832
  • +10
In production Digital Product Ecosystem

U-Like-It

Complete digital product ecosystem – app, merchant suite, backend and web platform.

An end-to-end ecosystem of mobile app, business features, cloud infrastructure and analytics pipelines – proof of complete SaaS and app development, not just individual frontends.

  • Mobile App
  • Web Platform
  • Backend
  • Cloud Infrastructure
  • +8
In production Generative AI

AI Content Factory

Automated video production pipeline based on multiple orchestrated generative AI models.

From briefing to finished video clips: specialized AI models for text, image and video generation are combined into an automated, controllable production process.

  • Generative AI
  • LLMs
  • Image Generation
  • Image Editing
  • +4
04Getting Started

Three concrete ways to start

Defined work packages with a clear result – the usual path into an engineering engagement with Riegel Systems.

Getting started

Architecture Sprint

Analysis of a product idea or an existing architecture.

  • Target architecture
  • Technical risks
  • Technology selection
  • Implementation recommendation
Discuss your project
Getting started

AI Proof of Concept

Fast, technically sound validation of a concrete AI use case – from data access to a working prototype.

  • Evaluated use case
  • Working prototype
  • Evaluation criteria
  • Production roadmap
Discuss your project
Getting started

Product MVP

From idea to a first production-ready version – with clean architecture instead of prototype debt.

  • Production-ready MVP
  • Cloud/CI infrastructure
  • Observability
  • Clear expansion stages
Discuss your project

Discuss your project

Briefly describe your project – we assess technical feasibility, effort and the best entry point.

Discuss your project Get to know our engineering