Inquiry icon START A CONVERSATION

Share your requirements and we'll get back to you with how we can help.

Thank you for submitting your request.
We will get back to you shortly.

Ensuring Secure Remote Work Environments

Client

US-based technology-enabled global business services company specializing in customer engagement and business performance.

Industry

Technology

Overview

We developed an AI/ML-powered computer vision-enabled monitoring solution that secures remote work environments. The solution uses facial recognition technology for user authentication and raises alarms when business rules are violated, ensuring data security and improved visibility into contact center operations.

Show More Show Less

Business Challenge

The crisis brought about by the COVID-19 pandemic resulted in professional services companies requiring their staff to work remotely. With a majority of their workforce working from home, our client faced challenges in ensuring data security and compliance.

The scenario accelerated the need for a secure computer vision-aided off-premises system that would meet the standards expected from an office environment. As data security plays a critical role in contact center operations, there was a need to monitor the presence of unauthorized personnel, mobile devices, books, and blacklisted objects in remote workspaces.

The client required a solution to authenticate, monitor employees, and deliver real-time violation alerts.

QBurst Solution

The solution detects, tracks, and verifies human faces in real-time with the help of deep learning neural network architecture to process data models. The anti-spoofing model prevents false facial verification by using a substitute (photo, video, mask) of an authorized person’s face.

Verification checks are performed during login and at regular intervals. The solution also detects objects or devices that are not permitted in the workspace, preventing unauthorized data capture.

Business Benefits

  • Remote workspace monitoring capabilities offered a high level of visibility into contact center operations and ensured data security
  • 98.75% reduction of GPU utilization cost (from $1600 to $20 per frame) for image processing due to advanced optimization using Docker-container architecture
  • Improved productivity: Computer vision aided monitoring reduced workspace distractions and resulted in higher productivity after implementation
  • High level of transparency, compliance, and risk management for stakeholders
  • Increased flexibility and scalability: Ability to operate 24X7 and scale up or down based on demand

Technologies

  • .NET
  • Angular
  • AWS
  • Docker
  • Kubernetes
  • TensorFlow

Business Challenge

The crisis brought about by the COVID-19 pandemic resulted in professional services companies requiring their staff to work remotely. With a majority of their workforce working from home, our client faced challenges in ensuring data security and compliance.

The scenario accelerated the need for a secure computer vision-aided off-premises system that would meet the standards expected from an office environment. As data security plays a critical role in contact center operations, there was a need to monitor the presence of unauthorized personnel, mobile devices, books, and blacklisted objects in remote workspaces.

The client required a solution to authenticate, monitor employees, and deliver real-time violation alerts.

QBurst Solution

The solution detects, tracks, and verifies human faces in real-time with the help of deep learning neural network architecture to process data models. The anti-spoofing model prevents false facial verification by using a substitute (photo, video, mask) of an authorized person’s face.

Verification checks are performed during login and at regular intervals. The solution also detects objects or devices that are not permitted in the workspace, preventing unauthorized data capture.

Business Benefits

  • Remote workspace monitoring capabilities offered a high level of visibility into contact center operations and ensured data security
  • 98.75% reduction of GPU utilization cost (from $1600 to $20 per frame) for image processing due to advanced optimization using Docker-container architecture
  • Improved productivity: Computer vision aided monitoring reduced workspace distractions and resulted in higher productivity after implementation
  • High level of transparency, compliance, and risk management for stakeholders
  • Increased flexibility and scalability: Ability to operate 24X7 and scale up or down based on demand

Technologies

  • .NET
  • AWS
  • Kubernetes
  • Angular
  • Docker
  • TensorFlow

More Stories

More Stories