Ensuring Secure Remote Work Environments

Scalable Remote Workforce Management: Vision-Powered Transparency & Risk Management

Client Profile

A company headquartered in the United States that specializes in using technology to provide worldwide business services focused on enhancing customer interaction and optimizing business operations.

Category

Generative AI

Project Overview

Our team has created an advanced monitoring system for remote work environments, integrating AI/ML and computer vision capabilities. This innovative solution employs facial recognition technology to authenticate users and triggers alarms whenever there are breaches of predefined business rules. This not only enhances data security but also provides a heightened level of insight into contact center operations.

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Business Challenge

The COVID-19 pandemic led many professional services firms to shift their teams to remote work. For our client, this posed challenges in ensuring data security and compliance with employees working from home. They urgently sought a secure off-site system using computer vision to maintain office-level standards. With data security crucial, especially in contact center operations, the focus was on monitoring remote workspaces for unauthorized individuals, mobile devices, restricted materials like books, and prohibited items. The client needed a solution to verify employees, keep a constant watch, and immediately alert for any breaches.

THE MAVA PARTNERS SOLUTION

This system uses advanced neural networks to swiftly identify, monitor, and confirm human faces as they appear in real-time. Its deep learning architecture processes data models to achieve this. Additionally, it includes a safeguard against fraudulent attempts to use substitutes like photos, videos, or masks to falsely verify a person’s identity.
Authentication procedures take place both during login and at set intervals to ensure ongoing verification. Moreover, the solution has the capability to identify and block objects or devices that aren’t allowed in a particular workspace, effectively preventing unauthorized data collection.

Positive Outcomes for Business

  • Enhanced oversight of contact center activities through remote workspace monitoring ensured robust data security and provided extensive visibility into operations.
  • Significantly slashed GPU utilization costs by 98.75% through sophisticated optimization leveraging Docker-container architecture, dropping expenses per frame from $1600 to a mere $20 for image processing.
  • Implemented computer vision-based monitoring to minimize disturbances in the workspace, consequently boosting productivity notably post-implementation.
  • Delivered a substantial level of transparency, compliance adherence, and effective risk management for all stakeholders involved.
  • Attained heightened adaptability and scalability, enabling seamless 24/7 operations and the flexibility to adjust resources based on varying demands.

Technologies

.NET
AWS
Kubernetes
Angular
Docker
TensorFlow

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