Introduction & Role at viAct
Could you briefly introduce yourself and share your role at viAct?
I am Hugo Cheuk, COO and Co-Founder of viAct. My background is in Building Engineering, and I have spent my career working closely with construction professionals to improve project delivery, workplace safety, and operational performance.
At viAct, I oversee business operations and growth while working with project owners, contractors, and safety teams to deploy AI-powered solutions across construction projects. Our focus is on helping construction organizations gain real-time visibility into site conditions. This enables them to prevent incidents, improve compliance, and enhance productivity through actionable intelligence.
The Inspiration Behind viAct
What inspired viAct’s mission to transform construction safety and operations through AI?
The inspiration behind viAct comes directly from our experiences as Building Engineering students and future construction professionals. Our CEO and Co-Founder, Gary Ng, and I were classmates in university. During our studies and early industry exposure, we spent considerable time observing construction projects and interacting with frontline workers. We saw firsthand how physically demanding and inherently risky construction environments can be.
What struck us most was that when incidents occurred, it was often frontline workers who bore the greatest consequences. In many cases, these incidents were not caused by a lack of effort from safety teams, but by the limitations of traditional monitoring methods and the inability to identify risks quickly enough.
“As engineers, we believed there had to be a better way. We began exploring how emerging technologies such as computer vision and artificial intelligence could help construction teams detect unsafe conditions in real time.”
That conviction ultimately led to the creation of viAct. Our mission has always been to make construction sites safer, smarter, and more efficient by transforming everyday site data into real-time operational intelligence that empowers project and safety teams to act before incidents occur.
Challenges in Modern Workplace Safety & Productivity
From your perspective, what are the biggest challenges currently facing the construction industry in terms of workplace safety and productivity?
One of the biggest challenges facing construction today is the growing volume of data coupled with a lack of meaningful consolidation.
Many projects have already embraced digital technologies. Sites are equipped with CCTV systems, access control systems, sensors, digital reporting tools, BIM platforms, and various safety management solutions. However, these systems often operate independently, creating fragmented streams of information.
The challenge is no longer collecting data; it is connecting and interpreting that data effectively.
Safety managers and project teams frequently need to switch between multiple systems to understand what is happening on site. As a result, critical risks may not be identified quickly enough, and opportunities to improve productivity can be overlooked.
At the same time, the industry is experiencing significant interest in AI. However, deploying individual AI tools without a unified framework can simply create additional layers of complexity. The real opportunity lies in consolidating site intelligence into a single operational view that enables teams to understand risks, compliance status, workforce activities, and project performance in real time.
The Proactive Shift in Safety Culture
How is AI changing the way construction companies approach workplace safety today?
AI is fundamentally shifting construction safety from a reactive discipline to a proactive one.
Traditionally, safety management relied heavily on manual inspections, periodic audits, and incident investigations. While these practices remain important, they often identify issues after risks have already emerged. AI enables continuous monitoring of site conditions, allowing project teams to detect unsafe behaviors, compliance violations, and emerging hazards in real time.
Today, construction companies are increasingly leveraging AI through:
- CCTV-enabled video analytics to monitor spatial risks.
- Connected IoT devices and smart wearables to track worker biometrics and positioning.
- Automated digital workflows to instantly log safety compliance data.
These technologies provide continuous visibility across large and complex sites that would otherwise be difficult to monitor consistently. The result is a more data-driven approach to safety management—one where risks can be identified, assessed, and addressed before they escalate into incidents.
Understanding Computer Vision in Construction
viAct is known for its AI-driven safety monitoring solutions. Can you explain how computer vision technology works in a real-world construction environment?
In a real-world construction environment, computer vision acts as an always-on digital safety observer. The technology utilizes existing CCTV infrastructure deployed across a project site. AI models continuously analyze video streams to understand what is happening on the ground, whether that involves worker movements, equipment operations, material handling activities, or compliance with safety procedures.
For example, the system can automatically identify whether workers are wearing required PPE, detect unauthorized entry into restricted areas, monitor safe distancing from heavy machinery, or recognize hazardous conditions that require immediate attention.
However, modern construction intelligence extends beyond computer vision alone. At viAct, we combine CCTV-enabled video analytics with IoT technologies such as smart helmets, connected watches, environmental sensors, and location-aware devices. These technologies provide additional contextual information about worker wellbeing, environmental conditions, and site activities.
The Next Evolution: Vision Language Models (VLMs)
More recently, the industry has begun evolving from traditional computer vision toward Vision Language Models (VLMs). VLMs enable AI systems to interpret visual information and contextualize it through Large Language Models (LLMs).
Instead of simply identifying objects or events, the system can understand broader operational contexts, summarize observations, explain potential risks, and generate actionable recommendations for project teams. This transforms AI from a monitoring tool into an intelligent operational assistant.
Common Risks Managed by Construction AI
What are some of the most common safety risks that AI can help detect and prevent on construction sites?
Construction sites are dynamic environments where multiple risk factors often interact simultaneously. AI is particularly valuable because it can continuously monitor these complex conditions at a scale that would be difficult to achieve through manual supervision alone.
The most critical risks AI can help detect and prevent include:
- PPE Non-Compliance: Missing helmets, safety vests, gloves, or protective eyewear.
- Work-at-Height Violations: Workers operating near dangerous edges without proper fall protection.
- Machinery Proximity Risks: Unsafe interactions involving cranes, excavators, loaders, and mobile machinery.
- Zone Violations: Unauthorized access to restricted or hazardous areas.
- Material Handling: Unsafe lifting and volatile material handling practices.
- Housekeeping Hazards: Slip, trip, and fall hazards caused by site congestion.
- Worker Wellbeing: Fatigue and heat stress concerns identified via connected wearables.
- Environmental Risks: Excessive heat, poor air quality, elevated noise levels, or hazardous gas exposure.
- Unreported Near-Misses: Capturing leading indicators that traditionally go unregistered.
Real-Time Hazard Detection vs. Traditional Safety Monitoring
How does real-time hazard detection improve incident prevention compared to traditional safety monitoring methods?
The fundamental difference is timing.
Traditional safety monitoring is often periodic and reactive. Safety officers conduct inspections, review reports, investigate incidents, and implement corrective actions. While these processes are essential, they are inherently limited by human capacity and the fact that observations are made at specific points in time.
Real-time hazard detection changes this dynamic by enabling continuous situational awareness across the entire project site. AI systems can monitor multiple locations simultaneously, identify unsafe conditions as they emerge, and immediately notify relevant personnel for intervention.
If a worker enters a restricted zone or operates at a height without appropriate protection, the system generates an alert within seconds. This rapid response prevents project disruptions and regulatory violations before they occur.
Global Market Adoption of ConTech Solutions
In your experience, how receptive are construction firms to adopting AI-based safety technologies?
The level of adoption varies across regions, but the overall trajectory is unmistakably positive.
Historically, some construction firms—particularly in parts of Asia and emerging markets—approached AI adoption cautiously. Cost considerations, uncertainty around return on investment, and concerns about operational disruption were common barriers. Many organizations viewed AI as an experimental technology rather than an operational necessity.
However, that perception is changing rapidly.
Through our deployments across multiple countries, we have observed growing demand from contractors, developers, and project owners. Increasing regulatory expectations, labor shortages, rising project complexity, and the availability of existing CCTV infrastructure have all accelerated adoption.
“A few years ago, companies primarily asked whether AI worked. Today, they are asking how quickly it can be deployed and how it integrates with existing workflows.”
Driving Productivity Beyond Site Safety
Beyond safety, how can AI and automation improve operational efficiency and productivity on construction projects?
While safety is often the initial driver for AI adoption, the operational benefits can be equally significant.
Construction projects generate vast amounts of information every day—from workforce activities and equipment movements to site logistics and progress updates. AI enables organizations to convert these manual, delayed data streams into real-time operational intelligence.
For example, AI can help monitor workforce utilization, track equipment productivity, identify bottlenecks in site logistics, verify work progress, and highlight deviations from planned activities. Automation also reduces administrative burdens by generating reports, documenting observations, and streamlining compliance processes.
The next evolution is the emergence of AI agents powered by VLMs and LLMs. These systems interpret site conditions, correlate information from multiple sources, and provide contextual recommendations. Instead of reviewing hours of footage, project managers can simply ask natural-language questions to uncover safety anomalies and workflow disruptions.
Empowering Faster On-Site Decision-Making
How does viAct help project teams make faster or more informed decisions on-site?
One of the biggest challenges on construction sites is not the lack of information—it’s the ability to convert information into actionable decisions quickly enough.
viAct addresses this by creating a unified intelligence layer across the project. Instead of requiring teams to review multiple CCTV feeds, safety reports, inspection records, and operational dashboards, our AI continuously analyzes site activities and highlights what truly requires attention.
Through computer vision, IoT integrations, and AI-powered analytics, project teams receive real-time alerts, automated observations, trend analyses, and risk assessments. This significantly reduces the time between observation and intervention, enabling faster and more informed decision-making across safety, operations, and project management functions.
Data Integration & Effective Risk Mitigation
What role does data play in modern construction management and risk mitigation?
Data has become one of the most valuable assets in modern construction.
Historically, many project decisions were based on periodic reports, manual inspections, and individual experience. While expertise remains critical, today’s projects are becoming too large and complex to manage effectively through manual processes alone.
Data provides objective visibility into site conditions, workforce behavior, equipment utilization, environmental factors, and project performance. When analyzed correctly, it allows organizations to move beyond assumptions and make evidence-based decisions.
From a risk mitigation perspective, data helps identify patterns that may otherwise go unnoticed. However, the true value lies not in collecting more data but in connecting and interpreting it.
High-Growth Sectors in the Construction Industry
Are there specific infrastructure or construction sectors where you see the fastest adoption of AI technologies?
We are seeing strong adoption across sectors where projects are large, complex, highly regulated, and carry significant safety and financial risks.
Major infrastructure projects—including rail, metro, tunnel, airport, highway, and bridge construction—are among the most active adopters of AI-driven safety and operational technologies. These projects involve large workforces, multiple contractors, and demanding compliance requirements, making real-time visibility particularly valuable.
We are also seeing significant momentum in large-scale commercial developments, industrial facilities, data centers, energy projects, and public-sector infrastructure programs. In many cases, project owners are increasingly incorporating digitalization and AI requirements into procurement and project delivery frameworks.
Real-World Case Studies & Measurable ROI
Can you share a real-world example where viAct’s technology delivered measurable improvements in safety or operational performance?
One example comes from a large-scale infrastructure project where the client sought greater visibility into safety compliance and high-risk site activities across multiple work zones.
By deploying viAct’s AI-powered video analytics platform, the project team was able to continuously monitor PPE compliance, access control, work-at-height activities, and interactions between workers and heavy equipment. Instead of relying solely on manual inspections, safety managers received real-time alerts and trend analyses that enabled immediate corrective actions.
Over time, the project experienced a significant reduction in repeat safety violations and near-miss incidents, while also improving overall compliance performance.
What kind of ROI or business impact are companies typically seeing after implementing AI-driven monitoring systems?
While ROI varies depending on project size and scope, the most immediate value comes from measurable improvements in safety performance.
Increasingly, these outcomes are becoming important beyond the construction site itself. Investors, regulators, and project owners are placing greater emphasis on Environmental, Social, and Governance (ESG) performance. Workplace safety is a critical component of the “Social” pillar, making safety performance an important business indicator rather than merely a compliance requirement.
Unexpected Benefits & Cultural Evolution
Have you observed any unexpected benefits from AI adoption in construction environments?
One of the most surprising outcomes is how quickly AI becomes an operational decision-support tool rather than just a safety solution.
Once site teams begin receiving continuous visibility into project activities, they discover unexpected opportunities to optimize workforce deployment, site logistics, equipment utilization, and subcontractor performance.
Another unexpected benefit is cultural. Because AI provides consistent and objective observations, safety discussions become more data-driven and less subjective. This fosters greater accountability and collaboration between project teams, supervisors, and contractors, ultimately strengthening the overall safety culture of the project.
Future ConTech Trends Over the Next 5 Years
What emerging ConTech trends do you believe will shape the future of the construction industry over the next five years?
The most transformative trend will be the rise of AI Agents and autonomous construction intelligence systems.
Over the past few years, the industry has focused heavily on digitization—deploying cameras, sensors, software platforms, BIM systems, and connected devices. The next phase will focus on making sense of all that information.
AI Agents powered by Vision Language Models (VLMs) and Large Language Models (LLMs) will fundamentally change how construction projects are managed. Instead of merely presenting dashboards and reports, these systems will actively analyze project data, identify risks, investigate incidents, recommend actions, and provide contextual insights through natural-language interactions.
The Collaborative Future of Human Workers and AI
How do you see the relationship between human workers and AI evolving on construction sites?
I firmly believe AI should empower workers, not replace them.
I remember visiting a construction site in Singapore and having a conversation with a frontline worker during a break. He had been in the industry for many years and understood the risks of the job better than most. During our conversation, he told me something that stayed with me:
“Most accidents don’t happen because people want to take risks. They happen because we’re busy, tired, distracted, or simply don’t see the danger in time.”
That observation resonated deeply with me because it highlighted a reality of construction work. Even experienced workers can miss a hazard when they are focused on completing a task.
This is where AI plays its role. AI does not get distracted, tired, or overwhelmed by the volume of activity on a site. It cannot replace the experience, judgment, and practical knowledge that workers bring to a project every day, but it acts as an ideal digital safety companion.
Standardizing AI Safety Industry-Wide
Do you think AI-driven safety monitoring will eventually become a standard requirement across the industry?
Yes, I believe it will become an industry standard, much like CCTV systems, digital reporting tools, and Building Information Modelling (BIM) have become increasingly common over time.
The construction industry faces growing pressure from regulators, project owners, insurers, and investors to demonstrate stronger safety performance and greater transparency. Under these conditions, relying solely on manual monitoring becomes increasingly difficult. AI provides continuous visibility and scalable oversight that traditional approaches cannot easily achieve.
What’s Next for viAct?
What innovations or developments is viAct currently most excited about?
One of the developments we are most excited about is the evolution from individual AI applications toward a fully connected construction intelligence ecosystem.
Today, viAct already brings together multiple technologies, including CCTV-enabled computer vision, IoT devices, edge computing infrastructure, and advanced analytics. However, the next chapter is even more exciting.
We are actively developing an ecosystem of more than 300 specialized AI Agents designed to function as digital experts for different construction and industrial workflows. Rather than simply detecting events or generating alerts, these AI Agents will be capable of investigating incidents, analyzing trends, conducting compliance reviews, generating reports, and recommending corrective actions via our dedicated platform, viGent.
Strategic Advice for Hesitant Construction Firms
What advice would you give to construction companies that are still hesitant about digital transformation and AI adoption?
My advice would be simple: start with a problem, not with the technology.
Many organizations view AI as a large-scale transformation initiative that requires massive investment and radical organizational change. In reality, successful digital transformation often begins with addressing a single, specific operational challenge—whether that is PPE compliance, work-at-height monitoring, incident reporting, or productivity tracking.
The most successful adopters typically begin with a focused deployment, validate measurable outcomes, and then expand based on demonstrated value.
