Introduction: Eyeing the possibilities
One of the most powerful—and talked about—capabilities of artificial intelligence (AI) in industry today is the technology’s ability to analyze images, both static and video. When used in conjunction with closed circuit television (CCTV) cameras, these purpose-built AI applications enable computer systems to automatically capture and instantly extract meaningful insights from photographs and video imagery, training machines to understand the visual world in much the same way humans do. And the breadth of potential value creation enabled by visual AI technology is as vast as the industrial world itself: facility security, product quality, employee safety—the list is endless. Precedence Research predicts that the market for AI-enabled computer vision applications will reach $275B by 2033 ($93B of that from the U.S. alone), with a CAGR of 31.8% from 2024 to 2033.
There are about 1.5B surveillance cameras in use worldwide—in banks, retail stores, gas stations, factories, and countless other facilities. Of these, about 60-65% are commercial and public infrastructure installations. The vast majority of video imagery captured by these cameras is not used in any meaningful way, and if it is, it’s almost always after an event has taken place.
When integrated effectively with a company’s existing systems, AI-enabled visual technology provides real-time insights that allow users to understand and act on whatever is happening in their environments. Industry leaders are using visual AI today not only to identify current or impending issues, but also to anticipate challenges, mitigate risk, repair problems, and decide upon next-best actions once a current issue/situation has been resolved.
Use cases: Too many to comprehensively list
Visual AI technology amplifies the value and utility of a company’s existing camera infrastructure. The technology autonomously detects and analyzes objects and situations in the image or video feed and alerts users when real-time situations or problems need immediate attention—facilitating the reduction of accidents, strengthened security, and a better understanding of operations that lead to enduring efficiency and quality gains. But let’s get even more basic: What can Visual AI do? What are some of the day-to-day, essential questions the technology can answer?
Security
Visual AI can analyze the video feed of cameras stationed along your facility perimeters and recognize suspicious activity within designated areas. It will autonomously alert if humans are:
- Found in restricted areas during specified time windows
- Using entrances or exits outside normal business hours
- Too close to, or within, a pre-defined region of interest
Visual AI will immediately send alerts to security personnel based on the system configuration settings and will continue to identify the individual even if they move to another camera location.
Product Quality
Whether it’s food, automobiles, aerospace, or other manufactured products, the ability to autonomously scan and detect defects adds greatly to the operating efficiency and profitability of a company. That might be because performing these quality checks manually is simply too tedious to expect people to spend their days doing. Or it might be because in many cases—like auto paint finishes or aerospace manufacturing—the defects that matter are just too subtle or small to be discerned by human eyes.
AI-powered cameras excel at this sort of inspection. And not only can they identify issues undetectable by the human eye, these applications can also then take immediate action by automatically modifying a production process rate, temperature, or pressure to instantly stop the defect from continuing.
Health & Safety
Among the most prevalent use cases for visual AI are those that ensure workers are equipped with the right gear to stay safe in busy industrial environments. Visual AI will track, measure, and alert if a person is not wearing the proper personal protective equipment (PPE) such as boots, gloves, hair nets, hard hats/helmets, lab coats, safety glasses, safety vests, harness belts, etc.
Additional safety use cases include unsafe worker/vehicle interactions, employees approaching too close to moving equipment, or working beneath suspended loads.
Ergonomic injuries constitute a significant recurring problem in the workplace. Overexertion and repetitive motion injuries accounted for the majority of non-fatal injuries that resulted in missed work days—over 946,000 injuries in 2024-2025, with approximately 20% of these requiring an emergency room visit. To combat this, visual AI can analyze how bodies move in the workplace, including detecting if a person is bending incorrectly to pick up a box or object, which can contribute to either a repetitive stress injury or a sudden muscle strain that sidelines workers.
Visual AI models can also identify particular unsafe behaviors in your work environment, like flagging if a person is sitting on top of stacked boxes, jumping off a platform, or not holding onto a railing. These types of behaviors can and do lead to debilitating injuries, but visual AI can track them proactively so that supervisors know precisely how and when they happen and can act on this knowledge by reminding workers to practice “safety first” at all times.
Sales Support
Most people, when they see a camera in a retail establishment, assume that it’s there for theft deterrence; and that is certainly a valid use case. But far more impactful is using that real-time imagery to monitor and analyze retail sales activity. Visual AI can determine how long people stand in front of displays, what products they pick up and look at, whether they return, what they buy, etc. This empowers retailers to optimally choose which products to offer and where to position them, increasing sales and optimizing customer experiences.
Taking action based on real-time knowledge
The objective with visual AI is to convert passive cameras into active sensors. In the same way that humans react to situations and process information, AI models can autonomously process live feeds from video cameras. And based on the business or location where the cameras are located, Avathon’s visual AI technology can draw from more than 150 use cases to alert the appropriate people about what’s happening in the workplace. That could be a safety manager; a person responsible for the security of a location; an operations manager responsible for sales performance, or even the customer service manager making sure customers are being serviced properly.
Whether users build a business case on foregone accidents, more efficient operations, higher quality products, or more profitable sales, the time to ROI for visual AI applications can be measured in weeks rather than years, and the equipment needed to start realizing results is, more often than not, already installed.
Avathon and Nvidia: A partnership in visual performance
To further enhance its visual AI capabilities, Avathon recently announced a strategic initiative to integrate Nvidia’s Blueprint for Video Search and Summarization (VSS) capabilities into its video intelligence platform. This collaboration will help organizations in industrial and infrastructure sectors gain faster, more actionable insights from vast amounts of video data—enhancing safety, situational awareness, and operational efficiency.
Through the integration of NVIDIA’s Metropolis VSS blueprint and advanced video AI stack, Avathon’s platform empowers users to search, summarize, and analyze video footage using natural language. This breakthrough significantly reduces the time and effort required to identify anomalies, investigate incidents, and monitor activity across large-scale camera networks. This represents a major advancement for industries like manufacturing, energy, logistics, aerospace, and public safety—where hours of video today must be manually reviewed for compliance, incident detection, and operational optimization.
“Integrating the NVIDIA VSS blueprint into our platform accelerates our mission to make video a true decision-making tool,” said Avathon CEO Pervinder Johar. “For our industrial customers, it means faster risk detection, more effective monitoring, and ultimately, safer and more resilient operations.”
Conclusion: Seeing is believing
With AI-powered visual solutions, companies evolve from being reactive to proactive to predictive, realizing greater value at every step in the process. With use cases targeting high-value challenges across multiple business categories such as health and safety, energy, and manufacturing, visual AI allows users to hit the ground running to holistically and proactively improve safety, security, and product quality.
To learn more about Avathon’s Visual AI solutions, visit our website.
