Industrial AI.
No Buzzwords. Just ROI.
My proven methodology to identify the right use case, build a working pilot in two weeks, and roll it out into your production environment — whether RAG, computer vision, or predictive maintenance.
Data Aggregation
Historical logs & visual data
Discovery & Analysis
Every facility is unique. I start by visiting your factory floor. No suits, just an engineer who knows production. I identify your most pressing bottleneck (e.g., high scrap rates, manual measuring overhead) and analyze your available data.
- ROI feasibility check
- Data & document inventory
- Deployment concept (On-Premise / Cloud / Edge)
2-Week Pilot
I don't waste months. Within 14 days, I build a working prototype with your data — be it a RAG system over your documents, a vision model on your parts, or a predictive-maintenance model on sensor data. The output: concrete metrics you can understand in five minutes.
- Custom model or RAG pipeline
- Validation against your real data
Accuracy: 99.84% (F1-Score)
Inference Time: 12ms / Part
Your Infrastructure
On-Premise // Cloud // Edge
Integration & Scale
Once the pilot proves itself, I move the solution into production. Where exactly it runs depends on the use case: RAG systems on your own server with AD integration, vision models on edge IPCs at the line, predictive maintenance on sensor gateways. What they share: fully on-premise possible, no data handover, maintenance contract for ongoing support.
- Deployment in your chosen environment
- Monitoring & maintenance contract
- Documentation for your IT team