With video intelligence powered by agentic AI, you can ask natural language questions about uploaded videos and get answers within seconds. Organizations across media, security, insurance, and professional services are generating more video than their teams can review. Meeting recordings accumulate in shared drives, and security cameras capture weeks of unreviewed footage. Field inspection videos sit in object storage long after the initial review. The information inside these videos is often valuable: a design decision discussed three weeks ago, the exact moment a person arrived at a door, or the sequence of events leading to a vehicle collision. But accessing it has traditionally required watching hours of content manually. The alternative, building custom machine learning (ML) pipelines for each specific question type, demands significant development effort. Each new use case meant new development work:

In this post, we walk through the architecture and key patterns for building a video intelligence solution that accepts natural language questions and returns answers from video content. The solution uses an agentic architecture that decides at runtime which AWS services to invoke. For previously analyzed content, responses return in under a second. Initial analysis of new videos takes 5–10 minutes depending on length and services required. The complete implementation is available in the companion GitHub repository.

Rather than pre-building a fixed pipeline for each question type, we use the Strands Agents SDK to create a single AI agent that orchestrates Amazon Bedrock , Amazon Rekognition , and Amazon Transcribe based on what the user asks.

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