Engineer first.
Software developer second.
I don't believe in massive consulting slide decks. I believe in Python scripts, PyTorch models, and PLC integration that actually works on the shop floor.
Simon Kirchebner – independent AI consultant, process engineer by trade.
I have worked in the manufacturing industry for more than 10 years and currently spend my days as a process engineer. I know production from the inside: shift work, quality pressure, data that exists but nobody knows where, and machines that have run for 20 years and will run for another 20.
This background is the reason I started TyrolAI. Most AI consulting is delivered by people who have never stood next to a CNC machine at 2 AM during a quality crisis. I have. That is why my focus is on AI that actually works in daily operations – not in slide decks.
My current focus is on knowledge management with RAG systems. I have built TyrolAI Docs, my own enterprise RAG platform, as the foundation of my knowledge-management projects. I also consult on computer vision, predictive maintenance, and process optimization – drawing on my process-engineering background.
Based in Schwaz, Tyrol. I work with manufacturing companies across Austria and the DACH region – on-site when needed, remote when possible.
TyrolAI Docs
Enterprise RAG platform for industrial companies – on-premise, GDPR-compliant, with Microsoft SSO and document-level security. Based on IBM's OpenRAG, hardened for Austrian industry.
AI Literacy under EU AI Act Art. 4
ICO AI End User Certificate — issued by the International Certification Organization (ICO), 22.03.2025. Confirms basic knowledge of risks, legal frameworks, and effective use of generative AI in the EU.
My Mindset
Pragmatism over Hype
No blockchain, no general AI. I focus on deep learning models trained specifically for your exact industrial bottleneck.
Edge Native
Factory data stays in the factory. I deploy everything on local IPCs for zero latency and absolute data security.
Seamless Integration
AI models are useless if they don't talk to your machines. I build robust OPC-UA bridges to your Siemens & Beckhoff PLCs.
My Arsenal
I use the same open-source frameworks powering global tech giants, strictly tailored and compiled for maximum industrial performance.
PyTorch & TensorRT
Hardware-accelerated AI inference
Docker & Kubernetes
Containerized deployments on Edge IPCs
Python, C++ & Rust
Maximum performance where it matters
import torch
import tensorrt as trt
# Load industrial vision model
model = torch.jit.load("tyrolai_defect_detector.pt")
# Optimize for NVIDIA Jetson Edge
engine = trt.Builder(trt.Logger(trt.Logger.WARNING))
network = engine.create_network(1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH))
# Ready for sub 15ms inference
print("TyrolAI Edge Node initializing...")