The AI vision system is trained to recognize and adapt to boxes that are crushed, dented, or irregularly shaped. It calculates optimal grip points dynamically to ensure successful picks.

Yes, our AI excels at mixed pallet scenarios. It identifies each box type, calculates the best picking sequence, and adapts gripper settings on-the-fly without manual intervention.

Our Box Depal app handles cardboard boxes of virtually any size, from small shoeboxes to large shipping cartons. The AI adapts in real-time to different dimensions, weights, and stacking patterns.

Captic’s vision intelligence integrates seamlessly via standard industrial interfaces such as OPC-UA or Ethernet/IP. It can be deployed on embedded hardware or edge devices to work alongside existing PLCs and control systems.

Our AI is trained on millions of images to minimize false positives. The system provides confidence scores and can be tuned to your specific tolerance levels. Human override is always available.

Integration typically takes 2-4 weeks. We support OPC-UA and Ethernet/IP protocols for seamless connection to your existing PLCs and robot controllers. Our team provides full support throughout deployment.

Captic is designed for OEMs, machine builders, and integrators who want to make their systems smarter without developing AI in-house. It serves industries where flexibility, automation, and reliability are critical.

By reducing downtime, manual inspection, and false rejects, Captic helps OEMs and manufacturers achieve measurable productivity gains. ROI typically becomes visible within months after deployment.

Absolutely. Captic is optimized for real-time inference on edge hardware, ensuring high throughput with low latency, even in fast-paced industrial environments.

Deployment timelines depend on the application and complexity. Turnkey AI applications typically go live within 2–4 weeks, while more customized solutions may take 6–12 weeks. Thanks to Captic’s pre-trained models and modular architecture, deployments are significantly faster than building an AI solution from scratch.

Traditional vision systems rely on fixed rules and controlled conditions. Captic uses machine learning and adaptive computer vision to handle variability in products, lighting, and movement, making it robust in dynamic production environments.

You can book a demo with Captic’s team to explore real-world examples and discuss how our AI vision can enhance your machines’ adaptability and intelligence.

No. Captic can run fully on-premise for sensitive environments or offline operations. Cloud deployment is optional and used mainly for large-scale data aggregation and performance monitoring.

Yes. Captic is built with a modular architecture that allows customization for specific inspection, tracking, or automation needs. We can co-develop custom AI applications tailored to your use case, while keeping the core AI platform consistent and scalable.

Yes. Captic’s adaptive AI continuously learns from new visual data. When production changes: new product types, lighting, or layouts, the system updates automatically without extensive manual retuning.

Captic supports OPC-UA and Ethernet/IP protocols, making it easy to integrate with your existing PLCs and robot controllers without major infrastructure changes.

No, you don't need any ML expertise. Our platform is designed for OEMs and system integrators. We handle all the AI complexity – you just configure and deploy. Our team provides full support throughout the process.

We offer flexible pricing models including per-machine licensing, volume discounts for fleet deployments, and enterprise agreements. Contact us for a customized quote based on your specific needs and deployment scale.

Captic is built with data privacy and security at its core. All visual data is processed on-premise at the edge, so your operational data never leaves your facility unless you explicitly choose to share it. Customers retain full ownership of their data. Captic is SOC 2 compliant and follows industry best practices for industrial cybersecurity.