← All case studies
Media & entertainmentMedia search

AI Video Search

Find scenes by describing what you need. Help editors and content teams search a video archive, inspect the source moment and locate footage for reuse.

01

Search scenes with everyday language

02

Combine visual content with speech and metadata

03

Jump from a candidate match to the source moment

Video walkthrough · An illustrative scene-search walkthrough using sample video footage. Open video

Industry
Media & entertainment
Focus
Media search
Inputs
Video files, scene descriptions, transcripts and metadata
Teams
Editors, producers, content teams and archive managers

The business situation

Where this fits

Useful footage is often buried behind filenames and incomplete tags. Editors may remember what a scene looks like or what was said without knowing which file contains it. They need a search that works at the scene level.

For teams that need to retrieve useful moments from a growing video library without relying on exhaustive manual tagging.

  • Editors remember a scene but cannot locate its file.
  • Archive tags are incomplete or inconsistent.
  • Finding a short reusable clip requires watching long recordings.

The solution

How the solution helps

The archive-search workflow breaks video into searchable scenes and combines visual descriptions, speech and metadata. A natural-language query retrieves candidate moments that the user can inspect in context. This makes the archive useful for questions beyond file names and folder structures.

01

Index the archive by scene

Organise video segments with searchable visual, speech and metadata information.

02

Describe the footage you need

Use natural language to find candidate moments across the indexed material.

03

Inspect and reuse the source

Check the clip and timestamp before taking the footage into the next editorial step.

In practice

Find a scene for a new edit

Search for a described moment and inspect the matching source footage.

What goes in

Authorised video files, available metadata and a description of the scene needed.

  1. Prepare searchable scenes

    Associate segments with visual, speech and metadata information.

    OutputAn archive searchable below the file level.

  2. Retrieve candidate moments

    Search with the scene description and review the returned candidates.

    OutputA shortlist of relevant moments.

  3. Check the source

    Open the clip and timestamp to confirm it fits the editorial need.

    OutputA source moment ready for the team’s reuse process.

How it works

How the workflow comes together

Video preparation

Process source files into scenes, transcripts and metadata.

Search index

Combine text and visual representations in an archive index.

Search portal

Connect natural-language queries with candidate scenes and source playback.

  • Amazon S3
  • Video scene processing
  • Amazon Transcribe
  • Amazon Bedrock
  • Amazon OpenSearch Service

Customer value

What this means for your team

In the workflow

Search by the content of a scene

Editors can start with what they remember or need, then inspect candidate moments rather than opening files one by one.

Why it matters

A more useful video archive

Help content teams discover existing footage, reduce repeated viewing and make archive material easier to reuse.

Review and control

Keep people in control

  • Index only footage your organisation is authorised to use.
  • Review the source clip and context before selecting a result.
  • Keep rights, retention and access requirements part of archive management.

Get started

Start with your use case

Start with one archive collection and the scene searches editors repeat most often.

Useful starting information

  • An authorised sample video library
  • Representative editorial search questions
  • Archive access and rights requirements

Success measures to track

  • Relevance of retrieved scenes
  • Time spent finding suitable source footage
  • Coverage of the selected archive

Fit with your existing systems

Agree the source storage, indexing scope, metadata and route from a selected result into the editorial workflow.

View all
Telecommunications · Customer supportAI Customer Support for Telecoms
A customer-support walkthrough using sample conversations, subscribers and service records.Read the case study
Telecommunications

AI Customer Support for Telecoms

Connect customer conversations, account history and network issues so support teams can understand repeat contacts and review the right next action.

  • Find the reasons behind repeat calls
  • Bring account and service evidence into one view
  • Review service actions before they are carried out
Read case study
Technology · AI governanceAI Agent Governance and Cost Control
A representative walkthrough of agent ownership, activity, cost and review workflows.Read the case study
Technology

AI Agent Governance and Cost Control

Give AI platform teams a clearer view of agent ownership, activity and spending, with review workflows for budgets and policy decisions.

  • Connect each agent to an accountable owner
  • Review activity and spending in one place
  • Support budget reviews and audit preparation
Read case study
Maritime & offshore · Crew planningCrew Change Planning for Maritime Operations
An illustrative crew-change recovery walkthrough using sample planning records.Read the case study
Maritime & offshore

Crew Change Planning for Maritime Operations

Explore crew-change recovery options with availability, travel and eligibility information in one planning workflow, so duty controllers can review the next move.

  • Bring crew and travel constraints together
  • Compare options when a crew change is disrupted
  • Keep the duty controller in charge of the plan
Read case study

Your next conversation

What scenes do your editors wish they could find with a simple description?

Tell us how your team works today. We’ll explore the information, integrations and review process that fit your use case.

Discuss this use case