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videodb
VideoDB Documentation
  • Pages
    • Welcome to VideoDB Docs
    • Quick Start Guide
      • Video Indexing Guide
      • Semantic Search
      • How Accurate is Your Search?
      • Collections
      • Public Collections
      • Callback Details
      • Ref: Subtitle Styles
      • Language Support
      • Guide: Subtitles
    • Examples and Tutorials
      • Dubbing - Replace Soundtrack with New Audio
      • VideoDB x TwelveLabs: Real-Time Video Understanding
      • Beep curse words in real-time
      • Remove Unwanted Content from videos
      • Instant Clips of Your Favorite Characters
      • Insert Dynamic Ads in real-time
      • Adding Brand Elements with VideoDB
      • Eleven Labs x VideoDB: Adding AI Generated voiceovers to silent footage
      • Elevating Trailers with Automated Narration
      • Add Intro/Outro to Videos
      • Audio overlay + Video + Timeline
      • Building Dynamic Video Streams with VideoDB: Integrating Custom Data and APIs
      • AI Generated Ad Films for Product Videography: Wellsaid, Open AI & VideoDB
      • Fun with Keyword Search
      • AWS Rekognition and VideoDB - Effortlessly Remove Inappropriate Content from Video
      • Overlay a Word-Counter on Video Stream
      • Generate Automated Video Outputs with Text Prompts | DALL-E + ElevenLabs + OpenAI + VideoDB
    • Visual Search and Indexing
      • Scene Extraction Algorithms
      • Custom Annotations
      • Scene-Level Metadata: Smarter Video Search & Retrieval
      • Advanced Visual Search Pipelines
      • Playground for Scene Extractions
      • Deep Dive into Prompt Engineering : Mastering Video Scene Indexing
    • icon picker
      Multimodal Search
      • Multimodal Search: Quickstart
      • Conference Slide Scraper with VideoDB
    • Real‑Time Video Pipeline
      • Automated Traffic Violation Reporter
    • Meeting Recording SDK
    • Generative Media Quickstart
      • Generative Media Pricing
    • AI Video Editing Automation SDK
      • Fit & Position: Aspect Ratio Control
      • Trimming vs Timing: Two Independent Timelines
      • Advanced Clip Control: The Composition Layer
      • Caption & Subtitles: Auto-Generated Speech Synchronization
      • Notebooks
    • Transcoding Quickstart
    • director-light
      Director - Video Agent Framework
      • Agent Creation Playbook
      • How I Built a CRM-integrated Sales Assistant Agent in 1 Hour
      • Make Your Video Sound Studio Quality with Voice Cloning
      • Setup Director Locally
    • github
      Open Source Tools
      • llama
        LlamaIndex VideoDB Retriever
      • PromptClip: Use Power of LLM to Create Clips
      • StreamRAG: Connect ChatGPT to VideoDB
    • zapier
      Zapier Integration
      • Auto-Dub Videos & Save to Google Drive
      • Create & Add Intelligent Video Highlights to Notion
      • Create GenAI Video Engine - Notion Ideas to Youtube
      • Automatically Detect Profanity in Videos with AI - Update on Slack
      • Generate and Store YouTube Video Summaries in Notion
      • Automate Subtitle Generation for Video Libraries
      • Solve customers queries with Video Answers
    • n8n
      N8N Workflows
      • AI-Powered Meeting Intelligence: Recording to Insights Automation
      • AI Powered Dubbing Workflow for Video Content
      • Automate Subtitle Generation for Video Libraries
      • Automate Interview Evaluations with AI
      • Turn Meeting Recordings into Actionable Summaries
      • Auto-Sync Sales Calls to HubSpot CRM with AI
      • Instant Notion Summaries for Your Youtube Playlist
    • mcp
      VideoDB MCP Server
    • Edge of Knowledge
      • Building Intelligent Machines
        • Part 1 - Define Intelligence
        • Part 2 - Observe and Respond
        • Part 3 - Training a Model
      • Society of Machines
        • Society of Machines
        • Autonomy - Do we have the choice?
        • Emergence - An Intelligence of the collective
      • From Language Models to World Models: The Next Frontier in AI
      • The Future Series
      • How VideoDB Solves Complex Visual Analysis Tasks
    • videodb
      Building World's First Video Database
      • Multimedia: From MP3/MP4 to the Future with VideoDB
      • Dynamic Video Streams
      • Why do we need a Video Database Now?
      • What's a Video Database ?
      • Enhancing AI-Driven Multimedia Applications
      • Misalignment of Today's Web
      • Beyond Traditional Video Infrastructure
      • Research Grants
    • Customer Love
    • Team
      • videodb
        Internship: Build the Future of AI-Powered Video Infrastructure
      • Ashutosh Trivedi
        • Playlists
        • Talks - Solving Logical Puzzles with Natural Language Processing - PyCon India 2015
      • Ashish
      • Shivani Desai
      • Gaurav Tyagi
      • Rohit Garg
      • VideoDB Acquires Devzery: Expanding Our AI Infra Stack with Developer-First Testing Automation
Videos are inherently multimodal — they present both visual and audio content simultaneously, creating a unified experience. Our brains naturally use these modalities to store and retrieve information. With advancements in retrieval technology, we now have the opportunity to develop an assistant or agent that can mimic our cognitive processes for storing and retrieving information externally.
VideoDB allows you to index both spoken and visual content, creating a modular architecture optimized for multimodal search queries. This can significantly benefit your users by enabling them to:
Watch streams or footage instantly.
Extract information or content for their workflows.
Multimodal search and reasoning enable more human-like behaviors when retrieving information from videos. This approach offers various types of searches and solves a wide range of use cases. Let’s explore a few examples:

Watch the footage instantly: Multimodal Search in Action:

Show me the footage of the suspects being caught on camera stealing at the mall and the news anchor discussing their identities.
This query is a classic example of a multimodal search as it seeks both visual content (the footage of the theft) and spoken content (the news anchor's discussion). The search engine needs to process video data for visual evidence and audio data for the spoken segment, making it a multimodal search.
These kind of queries are common in many critical scenarios, for example:
Law Enforcement: Helps in quickly retrieving crucial evidence from vast amounts of surveillance and news footage.
Media and Journalism: Facilitates the process of locating specific segments within hours of news broadcasts, aiding in efficient reporting and fact-checking.
Public Safety: Enhances the ability of authorities to disseminate important information to the public by quickly identifying and sharing relevant content.
Check notebook for the implementation.

Extracting Content from the Screen: Enhanced User Experience

"What was on the screen when 'quantum entanglement' was spoken?"
Another powerful application of multimodal search and information retrieval lies in the ability to extract and share content displayed on screens. This feature is particularly useful for taking notes or sharing information with others, especially in dynamic and multimedia-rich environments. Some examples:
Educational Settings: A student is watching an online lecture and wants to capture the slide that was displayed when the professor mentioned "quantum entanglement."
Business Meetings: During a virtual meeting, a project manager wants to save the presentation slide that was shown when the team discussed "budget allocations."
Content Creation: A content creator is reviewing a webinar and wants to capture the visual content displayed when the speaker talked about "social media strategies."

In this section, you'll find tutorials, notebooks, and blogs designed to help you unlock the potential of multimodal video retrieval for your video library. These resources will empower your Retrieval-Augmented Generation (RAG) pipeline, enhance AI-driven video content creation, and optimize the search for multimodal information.


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