Agentic conversational video intelligence built on AWS

This article demonstrates how to build a conversational video intelligence system using agentic AI on AWS that answers natural language questions about video content by orchestrating Bedrock, Rekognition, and Transcribe services.

• Agentic architecture uses an LLM to decide at runtime which AWS services to invoke based on user queries
• Supports transcription-based queries, visual analysis, face matching, and comprehensive video summaries
• Caches analysis results for fast follow-up queries (under 1 second) while initial analysis takes 5-10 minutes
• Extends beyond video to documents, clinical notes, and other modalities by adding new tool functions
• Deploys on ECS Fargate with CloudFront, Cognito authentication, per-user S3 isolation, and threat modeling
• Reduces manual video review time by approximately 80% compared to traditional manual analysis

The agentic pattern eliminates fixed processing pipelines, enabling flexible multi-modal AI assistants that scale to new capabilities by adding tool functions without workflow logic changes.