Commercial Oversight Software

Software made operational Oct. 2025 and shipped to several clients

Case Study: Commercial Oversight Software

Background

In today's increasingly competitive business landscape, organizations across industries are recognizing the critical importance of maintaining operational excellence while ensuring the highest standards of workplace safety and employee performance. Traditional monitoring approaches often rely on manual oversight, periodic audits, and reactive measures that fail to capture the full scope of daily operations. This has created a significant gap between management's visibility into actual workplace conditions and the real-time dynamics that drive business success or failure. Companies need comprehensive, intelligent systems that can provide continuous, objective insights into their operations without compromising employee trust or workplace culture.

Challenge

Modern businesses struggle to maintain consistent oversight across their operations due to the limitations of traditional monitoring methods. Existing solutions often rely on outdated surveillance systems that provide basic recording without intelligent analysis, generate overwhelming amounts of data that require manual review, or fail to integrate seamlessly with existing business intelligence platforms. Furthermore, many systems lack the sophistication to distinguish between normal operational variations and genuine safety concerns or performance issues, leading to either alert fatigue or missed critical incidents that could impact business continuity.

Solution

Where traditional oversight falls short, we're pioneering the next generation of intelligent commercial monitoring through our comprehensive computer vision platform that transforms passive surveillance into active business intelligence, featuring:

Intelligent Visual Analysis

Employees are detected frame by frame from existing camera infrastructure, with each workstation defined as a fixed region and classified as occupied when it and an employee's bounding box exceeds a certain IoU overlap threshold.

Performance Analytics

Objective measurement of operational efficiency, workflow optimization opportunities, and employee productivity metrics that drive meaningful improvements.

Proactive Safety Monitoring

Real-time detection of safety violations, hazardous conditions, and compliance issues before they escalate into costly incidents or regulatory violations.

Privacy-First Design

Built with privacy by design principles, ensuring employee trust through transparent data handling and configurable anonymization features.

System Components

A cutting-edge model incorporating YOLO v26 and OpenPose finetuned and trained on data specific to any workplace.
Seamless integration with existing security systems, IoT sensors, and any unique business intelligence platforms.
Real-time alerting system with intelligent prioritization, reduce false positives, and ensure critical incidents receive immediate attention.
Customizable dashboard with role-based access controls, allowing any stakeholder to access relevant insights without feeling overwhelmed.
Optional predictive analytics engine that identifies trends and potential issues before they impact operations or safety.

Outcome: Shipped, and holding up on real office floors.

The system was made operational in October 2025 and has since shipped to several clients. The core result behind that decision: transfer learning onto a custom-labeled dataset lifted average precision on the employee-detection task from 69% using stock COCO weights to 98% on the deployment camera — the difference between a general-purpose person detector and one that reliably resolves seated, partially occluded employees at a fixed CCTV angle.

Employee detection and per-station occupancy tracking running on live office CCTV footage.

The clip shows the deployed pipeline end to end: employees detected frame by frame, each workstation resolved to occupied or vacant by overlap, and seated time accumulated against the footage's own clock. Since delivery, the detection stage has been rearchitected onto YOLOv26 with GPU acceleration, cutting inference cost per camera and clearing the way for the multi-camera and action-recognition work now in progress.