From Order to Machine: AI That Protects Your Delivery Dates
Manufacturers and suppliers across the DACH region work with tight delivery windows, fluctuating load and bills of materials that span several production stages. We connect your production planning (MRP), capacity scheduling and machine data in one system that traces the full path from a customer order to the individual machine. Multi-level bills of materials, variants and routings stay consistent even when quantities or due dates change at short notice.
At the centre sits our ESTAYA AI Platform. It provides a single LLM gateway, citation-grounded RAG with source references and a knowledge graph that links parts, batches, inspection records and suppliers. This keeps traceability under DIN EN ISO 9001 auditable: from a quality finding you can follow the bill of materials back to the affected batch and the machine that produced it. We run open-weight models such as Llama, Mistral or Qwen ourselves with vLLM on our own GPU systems in Germany. Your engineering, order and machine data stay inside your organisation.
Machines connect through established IoT protocols such as OPC UA and MQTT. Predictive maintenance builds on that sensor data: models detect anomalies in vibration, temperature or cycle time and flag impending failures before an unplanned stop puts your delivery dates at risk.
- Plan capacity realistically: surface work-centre bottlenecks early
- Safeguard quality: tie inspection data and findings to batch and machine
- Prevent downtime: catch abnormal machine behaviour before it stops the line
- Stay sovereign: data residency in Germany, no US cloud