RealTimeVisualAI

Client :  Confidential Multi-Departmental Organization 

Industry:  Surveillance & Analytics 
Location:  USA

A forward-thinking enterprise seeking to elevate its surveillance capabilities from passive monitoring to active intelligence using AI-driven video analytics.

 
 
“InfoObjects’ expertise in Generative AI helped us build an AI-powered evaluation module that delivers actionable insights in real time. It has transformed how we detect and respond to incidents, leading to measurable improvements in operational efficiency and employee engagement.”
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Vice President,
Corportae Event Management

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Overview

To modernize its video monitoring infrastructure, the client partnered with InfoObjects to build a real-time, scalable visual AI platform. The solution focused on turning raw video streams into structured, actionable insights—delivering accurate object detection, automated event logging, and seamless multi-stream processing to support cross-functional use cases.

60 %

Incident Response Time Reduced

75 %

Monitoring Efficiency Improved

90 %

Object Detection Accuracy

50 %

Manual Review Time Reduced

The Challenge

Despite a well-established video surveillance infrastructure, the organization faced several limitations:

  • Delayed Situational Awareness: Manual monitoring led to slow response times.
  • Underutilized Video Data: No structured system for converting footage into analytics.
  • Edge Case Blind Spots: Difficulty identifying rare or low-visibility events.
  • Lack of Scalability: No unified pipeline to support real-time analytics across departments.

The client needed a robust, AI-driven system to automate monitoring, detect anomalies, and provide insights at scale.


 

InfoObjects Solution

Real-Time AI-Powered Object Detection

InfoObjects deployed a YOLO-based (You Only Look Once) deep learning model optimized for fast and accurate object recognition. The solution was engineered for real-world operational scenarios:

  • Custom Dataset Creation: Manual annotation using CVAT, Roboflow, and internal tools to build domain-specific datasets.
  • High-Performance Model Training: Trained YOLO models using NVIDIA GPUs and optimized with TensorRT for ultra-low latency.

Intelligent Streaming Architecture

  • Live Video Integration: Real-time ingestion of RTSP streams via FFmpeg and OpenCV, with support for multi-stream environments.
  • Structured Logging: Captured and stored metadata—bounding boxes, class labels, confidence scores, and timestamps—into CSV/JSON formats for analytics and reporting.

Scalable, Auditable Infrastructure

  • Automated Recording: MP4 video capture enabled compliance audits and incident replay.
  • Cross-Functional Utility: Modular design supported applications across facilities, training, safety, and logistics.


The Result

InfoObjects’ real-time visual AI solution redefined how the client harnessed video surveillance:

  • Proactive Monitoring: Enabled faster, data-driven responses to operational events.
  • Enhanced Safety: Improved detection of critical incidents and rare events.
  • Operational Intelligence at Scale: Transformed passive footage into a strategic asset.
  • Future-Ready Architecture: Built a scalable foundation for expanding intelligent automation.

With AI embedded into their surveillance systems, the organization moved beyond traditional monitoring—unlocking a powerful edge in safety, efficiency, and operational insight.

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