Chile Mine Taps viAct’s AI to Revolutionize Site Safety

– How one of Chile’s largest mining operations used AI video analytics to overcome fragmented safety processes, improve compliance across multiple sites, and unlock over a million dollars in risk reduction, without changing a single piece of hardware or adding another member to the safety team.

In the highly endowed but rugged mineral belts of northern Chile, one of the region’s largest mining operations was quietly battling a critical issue. It was continuously escalating safety risks that weren’t being caught in time.

Despite adhering to strict regulatory frameworks and employing an experienced workforce, the mine faced an uncomfortable truth: its traditional safety monitoring methods were reactive, slow, and deeply fragmented across three sprawling sites.

Supervisors relied on manual audits and incident logs that were often outdated by the time they reached decision-makers. Near-misses in danger zones went unnoticed, PPE violations slipped through during shift changes, and safety team leaders lacked a unified picture of what was happening underground and above.

The result was a rising trend in risk exposure, lower workforce confidence, and growing pressure from insurers and regulators alike.

That’s when the mine turned to viAct for the provision of its intelligent video analytics AI for high-risk industries, to inject intelligence into their safety infrastructure.

At the end of 2024, the mine took its final step of integrating the use of AI-enhanced video insights into its safety operations. The solution didn’t require a massive overhaul. It seamlessly tapped into the mine’s existing CCTVs and IP camera infrastructure, transforming static footage into real-time intelligence.

But the real story lies in the impact that followed.

Let’s break down the 3 successful use cases that directly contributed to the mine achieving $1.2M in risk mitigation within 6 months.

Before the strategic implementation of AI across the mine, the time taken to detect and escalate a critical safety violation was a slow crawl, often more than 3 hours from the moment of breach to when action was taken.

By the time supervisors were alerted to a restricted zone entry or a proximity breach among workers and vehicles, the risk had already passed or, worse, escalated.

But here’s how the scenario altered post-deployment:

Response time plummeted from an average of 3.7 hours to just 58 minutes.

In less than six months, this new responsiveness prevented 14 high-risk incidents, many of which could have led to equipment damage or worker injury.

The estimated savings from these timely interventions totalled $310,000 — a direct financial impact derived from lower downtime, averted liabilities, and streamlined resolution processes.

In mining, one of the mandatory compliance requirements for survival is with personal protective equipment (PPE) standards. Yet, the mine had a chronic issue with inconsistent PPE adherence, especially during overnight shifts and in remote confined zones.

Supervisors and EHS teams struggled to catch violations in real time, and workers became accustomed to leniency.

Now, as advanced analytics through videos came on site,  the game changed by making PPE detection automated and zone-specific. AI CCTVs began flagging missing helmets, goggles, and reflective vests the moment a worker entered a critical zone without proper gear.

These detections were logged daily, visualized in the safety trend reports, and categorized by worker ID and shift. Within 12 weeks, PPE compliance improved from 63% to 91%, a shift that was not only measurable but visible across all sites.

Even more importantly, the time taken to resolve a reported PPE violation dropped from 6 hours to just 8 minutes. This rapid feedback loop, supported by data-driven accountability, led to an estimated $450,000 in risk avoidance, driven by reduced injury claims, fewer internal compliance warnings, and improved audit scores during third-party inspections.

Operating across three geographically dispersed sites created another challenge — fragmented visibility.

Site managers were often unaware of which zones had the highest risk exposure or which shifts consistently reported violations. Traditional safety audits were conducted in silos and lacked comparative metrics.

The lowest-performing sites could now be easily identified and addressed with targeted training or intervention.

Within four months, average Safety Scores across the three sites improved from 65 to 92. More than that, the data empowered weekly safety reviews, turning what was once a paperwork-heavy discussion into a live dashboard-driven strategy session.

Reported safety incidents across the sites dropped by 37%, contributing an estimated $440,000 in risk mitigation through lower insurance premiums, fewer penalties, and better contract compliance.

In just 6 months, viAct helped this Chilean mine achieve:

• $310K: Fast response & incident prevention

• $450K: Injury claim reduction from PPE compliance

• $440K: Lower insurance, inspection & rework costs

What began as a response to safety inefficiencies in the Chile mine, in 6 months, has evolved into a full-scale transformation of how the mine operates. With AI embedded into daily workflows, safety is no longer seen as a reactive checklist; it has become an intelligent, continuous process that informs every decision on-site.

In the coming months, the data generated through the centralized platform acting as the safety command centre (SCC) will do more than just flag risks. It will start predicting them.

With consistent access to trendlines, behavioral insights, and real-time reports, the EHS teams in 2025 can transform workplace safety not on instinct, but on evidence. The workforce, too, will see safety not as a rulebook, but as a living, evolving system they are an active part of.

The true benefit lies not just in fewer incidents or improved compliance, but in building a resilient, self-correcting ecosystem that grows smarter over time.

This Chilean mine’s transformation proves that safety, when powered by AI and data, becomes far more than a compliance metric — it becomes a strategic lever for performance, trust, and profitability.

The $1.2M in risk mitigation was not a one-time win. It was the byproduct of a deeper AI-driven safety mindset where it is treated as an ongoing process. Supervisors now make decisions based on live dashboards.

Workers operate in environments where risks are detected before they escalate. Industry leaders can evaluate performance with clarity, not just with reports, but with real-time safety intelligence.

This is what it looks like when AI doesn’t just monitor operations — it transforms them.

Intelligent video analytics system such as viAct’s is designed to integrate effortlessly with your existing CCTV or IP camera infrastructure. There’s no need for new hardware or expensive replacements. Once integrated, the system taps directly into the live video feeds and uses AI to interpret safety-related behaviors and risks in real-time.

The platform supports both edge and cloud-based processing, meaning it can operate even in remote or low-connectivity environments. With this plug-and-play architecture, safety intelligence becomes instantly available — without disrupting daily operations or requiring major infrastructural changes.

When a safety violation or risk is detected through the intelligent video feeds, the system immediately triggers real-time alerts through multiple channels, ensuring fast response and maximum visibility. These include:

• Instant SMS and Email Notifications to designated safety officers

• WhatsApp Alerts for convenient mobile updates, especially during off-site supervision

• On-site Buzzers or Visual Warnings that sound or flash alarms in the affected zones

• Dashboard-Level Escalations showing incident severity, location, and timestamped video evidence

Each alert is actionable and fully traceable, helping EHS teams respond faster and prevent risk escalation.

Data privacy and transparency are foundational to such system. The platform ensures compliance with strict privacy protocols to safeguard workers’ identities and uphold ethical AI practices. Here’s how:

• Face Blurring: Automatically obscures worker identities in video footage unless explicit consent is provided or required for compliance

• Privacy-Preserving AI Models: Trained to detect safety behaviors and violations — not identify individuals

• Transparent Data Handling: All data collection, processing, and retention is fully documented and auditable

• Role-Based Access: Only authorized users can view sensitive data or footage, with logs for every access point

• Edge Processing Capabilities: Allows video analytics to occur on-site, ensuring footage never leaves the premises if preferred

• End-to-End Encryption: Secures all data during transmission and storage to prevent unauthorized access

Deployment of  intelligent safety analytics typically takes only a few days, depending on the number of cameras and the complexity of the site. The system is designed for rapid onboarding with minimal technical dependencies — making it ideal for active sites that cannot afford extended downtime.

Once deployed, it provides continuous post-installation support including:

• Onboarding and training for EHS teams

• Dedicated technical support and system health monitoring

• Continuous updates to improve AI detection models

• Custom configuration of alerts, dashboards, and safety scorecards

AI models of viAct are specially trained on thousands of hours of worksite footage across high-risk industries like mining, construction, and manufacturing. This results in very high detection accuracy — often exceeding 95% for key safety events such as PPE non-compliance, zone intrusions, and hazardous behavior.

In fact, a safety supervisor shared:

“We were initially skeptical, but viAct’s AI system started flagging violations that even our supervisors missed. Within the first month, detection accuracy reached over 96%, and the real-time alerts helped us act faster than ever before.” — EHS Lead, Copper Mining Project, Northern Chile

The system also supports continuous learning. Over time, the AI becomes even more precise based on site-specific behavior patterns and feedback from safety teams. False positives are minimized through intelligent calibration, and each detection comes with video evidence to validate or dismiss it quickly.

Want to make a safety transformation with AI in your site like the Chile Mine?