WG Tech Solutions cuts safety violations by 28% with Ultralytics YOLO and Axelera’s AI Accelerator

Tracking and improving industrial manufacturing operations can be challenging, especially since many processes are still manual. This lack of visibility into operations often leads to hidden inefficiencies, like bottlenecks and underutilized labor, that are hard to spot.

For instance, safety and compliance checks, such as ensuring workers wear proper personal protective equipment (PPE) or that materials are handled and stacked correctly, are often done manually, making violations easy to miss in fast-paced environments.

To bridge these gaps, WG Tech Solutions developed WGDeepInsight, an AI-powered video analytics platform for continuous monitoring. By analyzing live video feeds using computer vision models like Ultralytics YOLO models, the platform provides real-time visibility into operations, helping teams observe, analyze, and improve their manufacturing processes.

Link to this sectionImproving factory productivity and safety using vision AI#

WG Tech Solutions is an edge AI company focused on building intelligent systems for real-world environments. They develop end-to-end AI solutions that combine custom hardware, AI models, and application software, which enables organizations to monitor, analyze, and improve operations directly at the edge.

Based in India, the company works across multiple industries such as manufacturing, automotive, agriculture, and medical systems, where real-time insights and on-site intelligence are critical.

Its core platform, WGDeepInsight, is designed to provide real-time visibility into operations through AI-powered video analytics. It powers use cases across security, surveillance, safety compliance, and quality inspection, letting users monitor activities, detect issues, and improve workflows directly at the edge.

By combining computer vision models with artificial intelligence of things (AIoT) capabilities, WGDeepInsight makes it possible for manufacturers to track activities, monitor compliance, and improve operational visibility across factory environments.

Link to this sectionWhy visibility breaks down in factory operations#

Monitoring factory operations at scale requires consistent visibility, but real production environments make that far from straightforward. Activities can vary across stations, workers typically handle different tasks throughout the day, and conditions can shift across distributed factory setups.

In many cases, factory teams still rely on manual observation and on-ground checks to track workflows. While such traditional methods can provide basic oversight, they limit insight into how work is actually being performed.

In other words, capturing accurate, unbiased time-and-motion data is challenging. This lack of data becomes more critical when safety and security are involved. Issues such as PPE non-compliance, unauthorized access, or incorrect material handling can be easily missed, and delayed responses make it harder to prevent repeat violations.

For example, WG Tech Solutions worked with a leading original design manufacturer (ODM) operating multiple factory facilities that faced similar constraints. Most of the ODM’s assembly processes were still manual, so monitoring productivity, safety, and compliance relied heavily on visual checks.

To optimize productivity and safety compliance, the ODM needed a more structured approach to capture reliable time-and-motion data, track standard operating procedure (SOP) compliance across stations, and detect safety and security violations.

They also needed a more effective way to deliver real-time feedback to the right teams. Without automation, scaling this level of visibility remained a key concern.

Link to this sectionSmarter factory monitoring and compliance with Ultralytics YOLO models#

WG Tech Solutions integrates Ultralytics YOLO models into its WGDeepInsight platform to enable key computer vision tasks such as object detection, object tracking, and instance segmentation. By applying these models to live video feeds, the platform allows teams to continuously monitor operations, capture accurate time-and-motion data, and identify inefficiencies in real time.

This approach was applied in a deployment with the previously mentioned leading ODM. WGDeepInsight was implemented using a hybrid setup, with Axelera Metis AI accelerators deployed at workstations and across the factory IT environment, with the Voyager SDK streamlining edge deployment at scale.

Ultralytics YOLO models’ vision capabilities were used to monitor operations across factory stations, track adherence to SOPs, and detect safety and security violations such as PPE non-compliance, unauthorized access, and improperly stacked materials.

Fig 1. An example of Ultralytics YOLO models being used to detect irregularly stacked boxes.

To support this, video data was collected from multiple workstations over a three-week period and annotated using a proprietary interface. This dataset was used to train and fine-tune Ultralytics YOLO models, including Ultralytics YOLO11 and Ultralytics YOLOv8, tailored to the factory environment.

The models were further enhanced with additional inference logic, parameter tuning, and optimization techniques to ensure reliable performance in real-world conditions. Once deployed, the platform enabled real-time monitoring and automated detection of violations, providing consistent, data-driven visibility into operations.

Link to this sectionWhy choose Ultralytics YOLO models?#

For WG Tech Solutions, Ultralytics YOLO models provided a strong foundation for building computer vision solutions that could be adapted quickly to different factory use cases. Their ability to deliver high-performance inference at the edge made them a great option for large-scale manufacturing setups, where low latency and continuous monitoring are critical.

Ultralytics YOLO models also offered flexibility across various export formats for deployment, including ONNX, PyTorch, and NCNN. This made it easier to integrate them with both edge devices and centralized systems for a hybrid architecture.

Overall, by using Ultralytics YOLO models, WG Tech Solutions was able to deliver tailored solutions faster while maintaining reliable performance across large-scale factory environments.

Link to this sectionWGDeepInsight reduced worker violations by 28% with Ultralytics YOLO#

Using Ultralytics YOLO models, WG Tech Solutions’ WGDeepInsight platform provides continuous monitoring and analysis of factory operations, improving safety, compliance, and operational visibility.

In the case of the leading ODM, worker safety violations decreased by 28%. Real-time alerts, processed on-device with low latency, led to faster response times and fewer repeat issues, resulting in more consistent enforcement of safety protocols across the factory floor.

The platform tracked SOP adherence across stations and flagged violations as they occurred. It also identified issues such as incorrect PPE usage, unauthorized access, overcrowding, and missed or incorrect process steps.

For instance, in tray handling workflows, it verified whether items were picked and placed correctly and whether each step followed the required sequence, flagging any deviations along the way.

Fig 2. Ultralytics YOLO models helping detect single-hand tray handling.

On top of this, it extended to other operational and security workflows. In CCTV monitoring rooms, the system tracked personnel presence in real time and triggered alerts if staffing levels dropped below required thresholds.

Meanwhile, in quality inspection workflows, it verified process sequences, reinforced the use of specified tools, and monitored time spent per task, flagging any deviations to maintain consistent standards.

Over time, these vision insights provided clearer visibility into where processes were breaking down and supported corrective actions through targeted training.

Alerting and feedback mechanisms were tailored to customer requirements, with flexible integration into existing factory workflows. Notifications were delivered through channels such as email, messaging systems, and role-based dashboards, making sure that relevant insights reached the appropriate teams in real time.

This also ensured that critical procedures were followed consistently, such as using the correct tools and maintaining minimum staffing levels in controlled areas. Ultimately, day-to-day operations became more consistent, strengthening compliance across the factory floor.

Link to this sectionExpanding real-time monitoring across factory environments#

As industrial automation evolves, computer vision is becoming central to improving visibility and consistency in manual operations. By customizing Ultralytics YOLO models, WG Tech Solutions plans to extend its WGDeepInsight platform across new factory environments and workflows.

This supports use cases ranging from safety and security monitoring to process-level checks on the factory floor. Combined with edge-based deployment, real-time analytics, and Axelera Metis edge AI accelerators, it provides scalable monitoring and consistent operational insights across manufacturing environments.

Exploring vision AI for your operational workflows? Check out our GitHub repository and licensing options to get started with Ultralytics YOLO models. Learn about applications like AI in healthcare and vision AI in manufacturing, and Edge AI Accelerators like the Axelera AI Export and Deployment | Ultralytics Docs