What we do
We automate development processes with AI agents: n8n workflows, automated software development with all frontier lab AI tools and local open source models, AI-based requirements engineering, RAG systems and MCP integrations. Human in the loop, always.
Requirements engineering and management, system architecture (SysML/UML) and usability engineering for complex technical products. Toolchain experience: DOORS/DXL, PTC Integrity, Polarion, Enterprise Architect, Jira/Confluence. Latest AI technologies adapted for AI System Engineering.
Embedded software for physical devices, hardware-related development, model-based engineering, and iOS/visionOS spatial computing solutions.
ISO 26262 up to ASIL D, SOTIF, Automotive SPICE, FDA / IEC 60601 medical certification support, DO-178B avionics. We make AI-accelerated processes audit-proof.
Track record
Our experience comes from some of the most complex technology systems in the world:
Medical
Requirements engineering, usability engineering and certification support (FDA, IEC 60601) for a cyclotron-based cancer-treatment system of a leading medical device manufacturer.
Automotive
Feature ownership for deep-learning object detection functions used in autonomous driving, for a global tier-1 supplier.
Automotive
System architecture and requirements for vacuum-less brake systems for highly automated electric vehicles, and pneumatic brake systems (ABS, ESC) for trucks.
Automotive
Software and system architecture, technical safety concept (ISO 26262) for a German tier-1 supplier.
Aerospace
Systems engineering for civil and military aircraft and helicopters. Mission computers and cockpit displays of military aircraft and helicopters. DOORS and Slides management system for the largest passenger airplane of the world.
Automotive
Requirements management and HMI software architecture for fully digital cockpits of German premium OEMs.
AI
Full AI automation of a consulting business: agentic n8n workflows, LLM-based automated software development, AI-based requirements engineering, processes for Physical AI.
Questions & Answers
Physical AI means artificial intelligence that perceives, understands and acts in the real, physical world: in vehicles, medical devices, aircraft and industrial systems. It combines machine learning with sensors, actuators and safety-critical embedded systems.
AI agents draft, analyze and trace requirements, keep specifications consistent across tools, and prepare compliance evidence automatically. Agentic AI needs structured input to take efficient action. Engineers stay in the loop for decisions and reviews. The result: dramatically less process effort with the same or better quality.
Automotive (ECUs, ADAS, brake systems, instrument clusters), Aerospace (avionics, aerospace devices), Medical Technologies (device certification, usability) and Telecommunications, plus AI automation and AI development setup for engineering organizations in any technical domain.
Remote-first from our EU base in Cyprus, with established collaboration across Germany, Austria and Switzerland: video conferencing, shared toolchains (DOORS, Polarion, Jira, Confluence) and clear requirements-based work packages. On-site presence where the project demands it.
News
Interested in our engineering support? We would like to hear from you.
