Products / CT-Vision
CT-Vision
A Video Analytics Platform to Transform Visual Data Streams Into Actionable Insights
CT-Vision
A Video Analytics Platform to Transform Visual Data Streams Into Actionable Insights
Products / CT-Vision
CT-Vision is a modular video analytics platform architected for enterprise-grade scalability and performance. Leveraging the COBRA (Content-based Image Retrieval Analysis) framework, the advanced platform combines sophisticated language and vision models to address the challenges of manual video analysis, data security risks, and integration complexity by providing automated video insights, enhanced data security with robust governance and security measures, and seamless integration with existing infrastructures and systems.
Business Challenges Solved
Content Discovery
Traditional systems struggle to locate specific content within video repositories.
Video Asset Management
Traditional systems struggle to locate specific content within video repositories.
Content Modification
Traditional systems struggle to locate specific content within video repositories.
Real-time Analysis
Traditional systems struggle to locate specific content within video repositories.
Key Features
CT-Vision delivers a comprehensive suite of features designed to maximize the value of enterprise video assets
Core Capabilities
Text-Based Video Scene Retrieval
Find specific scenes using natural language descriptions.
Custom Audio Classification
Identify and categorize audio elements with Whisper fine-tuning.
Keyword-Based Video/Scene Filtering
35% time saved, improved task item visibility.
Enhanced Analysis
Voice Over Dubbing
Automatically generate voiceovers in multiple languages.
Chapter Analysis
Break down videos into logical segments for easier navigation.
Custom Text/Metadata Classification
Categorize content based on specific company criteria.
Industry Applications
CT-Vision versatile architecture enables enterprise-grade solutions across multiple sectors
- Automated car damage claim assessment.
- Video KYC process optimization.
- Insurance underwriting acceleration.
CT-Vision vs. Classical Vision Approaches
Semantic Understanding
CT-Vision
Excels at comprehending and generating semantic meaning from visual scenes using textual representations, interpreting content based on broader contextual information beyond visual elements alone.
Classical Approaches
Excels at comprehending and generating semantic meaning from visual scenes using textual representations, interpreting content based on broader contextual information beyond visual elements alone.
Adaptability
CT-Vision
Adapts to new tasks with minimal task-specific training due to extensive pre-training on vast datasets, delivering continuous performance improvement over time.
Classical Approaches
Requires significant re-training or fine-tuning for new tasks or domains, with generally static learning that demands explicit re-training to improve.
Pattern Recognition
CT-Vision
Recognizes complex patterns and anomalies that traditional methods might miss, adapting recognition patterns based on situational changes.
Classical Approaches
Processes and recognizes well-defined patterns efficiently in consistent environments but lacks adaptability to dynamic or complex patterns and contexts.
Implementation Process
CT-Vision implementation follows a structured methodology designed for enterprise integration
Use Case Spotlights
Car Insurance Claim Automation
CT-Vision improves the insurance claims process by automatically analyzing and documenting the accident scenes via car-mounted footage. The system helps process and authenticate damage assessments. This automation reduces claim processing time, improves accuracy, and enhances policyholder satisfaction through faster resolution.
Asset Defect Detection
For utility companies, CT-Vision analyzes infrastructure asset footage to identify defects and operation risks. The system employs models using confidence estimation, crack/bend spotting, and maintenance requirements and potential hazards. This proactive approach minimizes downtime, reduces inspection costs, and enhances overall reliability.
Sports Video Highlight Extraction
CT-Vision automatically generates highlight reels from sports footage by identifying key moments using object tracking, event classifiers, and scene segmentation. The system removes dead time from the final content and summarizes full-capacity essential actions. This capability significantly reduces editing time while improving viewer engagement.
Why Choose
CT-Vision?
Ready to Improve Your Enterprise's Approach to Video Analytics
Contact our solutions team to learn more about CT-Vision and schedule a personalized demonstration.
