Funding
Funding not disclosed
Founders
Product
Problem
Manufacturing facilities often experience unplanned downtime, quality defects, and material waste due to limited visibility into equipment health and production anomalies. Traditional inspection methods struggle to detect microscopic flaws in photonic components, leading to reliability issues in high‑precision applications. Additionally, infrastructure owners lack integrated tools to assess climate‑related risks to assets.
Solution
Aurora delivers an AI‑driven automation platform that continuously monitors production lines, identifies anomalies in real time, and predicts equipment failures before they occur. The system combines robotic precision with cloud‑native high‑performance computing to enable smart visual inspection and quantum‑enhanced detection of invisible defects in optical fibres and photonic devices. Integrated GIS analytics evaluate climate risk impacts on physical assets, supporting proactive resilience planning. Aurora also provides digital education and training modules, leveraging Erasmus+ resources to upskill personnel in smart manufacturing and data‑driven decision making. By unifying these capabilities, the platform improves line efficiency, reduces waste, and enhances product reliability across diverse industrial sectors.
Target Audience
Primary customers are manufacturers of high‑precision hardware—such as photonics, aerospace, and electronics—who require advanced quality control and equipment reliability, as well as infrastructure managers and educational institutions seeking climate‑risk analytics and smart‑manufacturing training.
Features
- Real‑time AI anomaly detection that flags process deviations and quality issues as they arise
- Predictive maintenance models that forecast equipment failures using high‑frequency sensor data
- Smart visual inspection powered by computer vision and cloud HPC for rapid defect identification
- Quantum‑enhanced optical inspection (ABSTRAQ) capable of detecting microscopic flaws in photonic components
- GIS‑based climate risk analysis that maps environmental threats to infrastructure assets
- Robotic automation integration for precise, repeatable manufacturing operations
- Digital education and training suite (Erasmus+ supported) for upskilling workers in AI‑enabled manufacturing