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Robovision

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Robovision is a visual intelligence infrastructure designed for industrial settings, deeply embedding visual AI capabilities into edge devices and providing governance across the entire system lifecycle. Its core product, Indurion Suite, is engineered for long-term stable operation, supporting continuous execution of inspection tasks even without network connectivity to ensure uninterrupted production lines. All models, configurations, and data remain under customer ownership, eliminating vendor lock-in and cross-customer data pooling.

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What is Robovision?

Robovision delivers an industrial visual intelligence infrastructure, helping manufacturing enterprises tackle the growing challenges posed by increasing process diversity and defect complexity. Its Indurion Suite software platform enables customers—via a web browser—to independently train, deploy, and fine-tune AI models without writing any code, guided by process experts. The system automatically identifies production line deviations through drift detection (patent pending) and pushes verified configuration plans to all operational devices, significantly reducing fault response times. It has already been implemented in highly variable industries such as semiconductors, food manufacturing, and horticulture—for example, at Agrophoenix, where it achieves AI-based quality inspection of over 1,000 peaches per minute; at Qing Food, where it supports end-to-end seedling identification, picking, and planting on automated production lines; and at ISO Horti Innovators, where it enables precise core removal, cutting product waste by approximately 90%.

Key features

  • Through drift detection (patent pending), it quickly corrects production line deviations and automatically pushes validated configuration plans to all running devices;

  • It supports exporting complete configurations and full datasets, with open algorithm standards, ensuring customers fully own model and data intellectual property rights, while preventing data sharing between different customer accounts.

Use cases and audience

Industrial manufacturers, system integrators, equipment vendors, and quality control teams—especially suited for industries such as semiconductors, food processing, and horticulture that face high variability.

  • Maintaining inspection accuracy in semiconductor manufacturing, adapting to increasing process complexity and defect diversity.
  • Adapt visual intelligence to adjust inspection conditions in response to changes in raw materials and product forms during food processing
  • In the horticulture industry, adapt to biological variations across crops and seasons without additional manual intervention
Input

Visual data input from imaging devices (such as cameras); process parameters, quality standards, and historical defect samples provided by the customer.

Output

Real-time classification, measurement, and tracking results; adaptive inspection recipes; drift-detection alerts along with validated corrective measures.

Frequently asked questions

Can customers independently adjust the visual AI system?

Yes. The customer already has the tools to make more independent system adjustments, no longer relying on the vendor for every modification.

How is data and model ownership determined?

The customer fully owns their data and models; data is not shared across accounts, and exporting complete datasets and configurations is supported.

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