Case Studies
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Data Infrastructure
Explore how we built scalable data platforms and serverless architectures to enhance data processing, reporting, and AI-driven insights.
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Omniverse for Automation Simulation
Realistic simulation of autonomous mobile robots (AMRs) in Isaac Sim avoids costly and time consuming pilot projects.
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Synthetic Data
99% accuracy with only 15 real photos: Generative AI pipeline creating realistic defect data for training ML models on automotive door panels.
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BOM Analyzer
CB reverse engineering tool using computer vision: 98% accuracy in identifying surface mount components with line laser height measurement.
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Fast Automation Deployment
From concept to factory floor in weeks: Automatically testing screw torque & correct seating with Lidar measurements.
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Low Cost AGV
Modular AGV developed & built for under 80k€: Cost-effective automated guided vehicle for transporting yarn, bobbins, and sliver cans in textile manufacturing.
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Metal Scanner
Sub-millimeter scanning of welded railway components: High-precision measurement system for detecting deformations on large metal parts.
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RISC-V SoC Reference Architecture
Driving adoption of RISC-V in Automotive
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Ultrasonic AI
Detecting defects beneath the surface: AI-driven ultrasonic inspection system for aerospace components with enhanced internal defect detection.
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Mixed Medium Ethernet Switch
Modular PCB bridging different Ethernet standards: Supports 10BASE-T1S, 100BASE-T1, 1000BASE-T1, and 100BASE-TX for automotive applications.
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Single-Pair Ethernet PCB
Next-generation automotive networking: 10BASE-T1S prototyping platform enabling Ethernet-to-the-edge connectivity with Zephyr RTOS.
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Weld Detection
Computer vision for QA of welds on agricultural machinery: Reliable detection of missing or misaligned welds with 90% reduction in revision time.
Our Experience in AI & Manufacturing
We have worked with the earliest versions of OpenAI's GPT models at BMW. Since then we have used AI and AI agents to improve engineering processes, either directly through automation, or indirectly by providing the right insights at the right time.
Our experience in industrial automation, QA, and the manufacturing domain in general, make it possible for us to combine these tools into a powerful platform. But also, to start with the right use cases and prove that AI can add value.
At Siemens, we built a sales-supporting AI tool that suggests the right actions for each sales manager, derived from a massive graph of customers, OEMs, industry news, and internal data.
