Automating video analysis and behavioral insights extraction with Computer Vision, Gen AI, and serverless AWS architecture.
The Challenge
Our client, a leading analytics provider, needed to transform their manual video review process into an automated, scalable solution. Their team was spending countless hours manually reviewing video footage to extract behavioral insights and compliance metrics. They needed a solution that would address several key requirements:
- Automated processing to convert and analyze video content without manual intervention
- Multi-format support for various video formats (MP4, MOV, AVI, MKV, WebM, and more) from different recording devices
- Real-time analysis to process videos immediately upon upload for rapid insights
- Scalable architecture to support hundreds of concurrent video processing jobs
- Structured insights generation based on predefined business rules
- Cost optimization through serverless architecture
Our Solution
We designed and implemented a fully serverless, event-driven video analysis pipeline using AWS services, Computer Vision, and Gen AI models that automatically process video content, extract meta data, and generate structured behavioral insights.
Architecture
- Event-driven processing pipeline with S3 notifications triggering immediate processing
- Serverless Lambda functions orchestrating the entire workflow
- Multi-stage processing: format standardization, audio extraction, AI analysis, and report generation
- Infrastructure as Code using AWS CDK in TypeScript
- Segregated S3 buckets for each processing stage with lifecycle management
- Integration with Amazon Transcribe for high-accuracy speech-to-text
- Amazon Bedrock integration for advanced language understanding
- Custom prompt engineering for behavioral categorization
Development Process
- FFmpeg integration via custom Lambda layers for video processing
- Automatic format conversion for optimal compatibility across all major video formats
- Optimized video encoding parameters for faster processing
- Custom vocabulary configuration for industry-specific terminology
- Excel-based rule configuration for flexible analysis criteria
- Dynamic model selection based on content type
- Comprehensive error handling and retry mechanisms
Key Features
- Automated Video Processing: Supports a wide range of video formats with automatic conversion
- Advanced Transcription: High-accuracy speech recognition with timestamp synchronization
- Intelligent Analysis: Behavioral pattern recognition using AI models
- Comprehensive Reporting: JSON-formatted analysis segments for easy integration
- Monitoring and Observability: CloudWatch integration for real-time monitoring
- Security and Compliance: IAM-based access control with encrypted data storage
- Parallel Processing: Handle hundreds of concurrent video processing jobs
Expected Outcomes
The solution is designed to transform video analysis capabilities:
- Processing Time: Significant reduction in manual review time through automation
- Scalability: Capability to process numerous videos simultaneously
- Accuracy: Consistent analysis quality through AI-powered processing
- Cost Efficiency: Optimized operational costs through serverless architecture
- Insights Generation: Rapid behavioral insights generation from video content
- Integration: Seamless integration with existing business intelligence tools
Technologies Used
- Infrastructure: AWS CDK, TypeScript, CloudWatch
- Processing Layer: AWS Lambda, Amazon S3, S3 Event Notifications
- Media Processing: FFmpeg, Custom Lambda Layers
- AI & Analytics: Amazon Transcribe, Amazon Bedrock, Claude 4 Sonnet
- Development: Python 3.11, Pandas, Jest, Pytest
- Security: IAM, Encryption, Audit Trails
