Updated on 19 September 2026
Physical AI: robot-learning data pipelines — pilot & R&D partners
CEO at Orange Hill Development d.o.o.
Belgrade, Serbia
About
Robots now learn from data, not hand-written code — and the bottleneck is high-quality data about how humans actually do physical work. Orange Hill (Vienna/Belgrade) is building the software layer between real-world work and robot training.
What we do:
- Capture: egocentric and wrist-camera recording protocols for real work environments (offices, facilities, light industry), with consent and GDPR-compliant anonymisation.
- Processing: 3D hand and body pose, camera trajectory, segmentation, sub-task and language labels, success/failure outcome labels.
- Delivery: training-ready datasets in LeRobot / RLDS formats for the NVIDIA Isaac / GR00T and open robot-learning ecosystems.
- Evaluation: measuring whether robot policies actually improve in real environments.
We are looking for:
- Industrial companies and facility operators willing to host a small pilot (a few operators, one site, 4–8 weeks).
- Robotics and embodied-AI teams that need task-specific human demonstration data or evaluation.
- Research partners for FFG, Eurostars or Horizon Europe project consortia.
Happy to meet at AAIC or talk online on 25 September.
Stage
- Concept
Topic
- Machine Learning
- Deep Learning Platforms
- Digital Twin/AI Modeling
- Image Recognition
Type
- Research
- Technical
- Financing
Organisation
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Tihomir Opacic
CEO at Orange Hill Development d.o.o.
Belgrade, Serbia
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We run your AI. You keep your data. — Sovereign AI platforms for industry & mid-market
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Stefan Hohla
CRO at headwAI GmbH
St. Florian am Inn, Austria
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High-Quality Data Annotation & Validation for AI
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Hans-Peter Kranewitter
Business Development & Sales at Responsible Annotation Services
Linz, Austria