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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
- 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 - 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
- Open Source Tools
  LlamaIndex VideoDB Retriever
  PromptClip: Use Power of LLM to Create Clips
  StreamRAG: Connect ChatGPT to VideoDB
- 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 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
- 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
- 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
  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

videodb

VideoDB Documentation

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AI-Powered Meeting Intelligence: Recording to Insights Automation

AI-Powered Meeting Intelligence: Recording to Insights Automation

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Copy JSON

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Goal:

This workflow automates the complete meeting lifecycle from recording to analysis and distribution. It processes different meeting types (Sync, Planning, Interview, Sales) and distributes insights to Slack, Coda, and HubSpot based on the meeting context.

The workflow handles different meeting types with intelligent branching instead of requiring separate workflows for each type.

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Prerequisites:

N8N Instance: Running N8N automation platform (cloud or self-hosted)

VideoDB API Key: Obtain from VideoDB Console

VideoDB N8N Node: Install the custom node in your N8N instance

Meeting Platform: Platform with bot recording support (Zoom, Teams, Google Meet)

Slack Workspace: With bot permissions for notifications

Coda Workspace: With API token for meeting documentation

HubSpot Account: With API key for sales meeting integration

Main Workflow Steps:

Step 1: Meeting Recording

Form trigger collects meeting URL and meeting type (Sync/Planning/Interview/Sales)

VideoDB joins the meeting and records the session

Wait for meeting completion before processing

Step 2: Video Processing

Index spoken words from the recorded meeting

Generate transcript with speaker identification and mapping

Process video content for analysis readiness

Step 3: AI Analysis with Branching

Switch workflow based on meeting type selection

Apply custom AI prompts for each meeting type:

Planning: Extract strategic outcomes, decisions, and action items

Interview: Generate candidate evaluation with recommendation

Sales: Identify deal details, stage, amount, and next steps

Sync: Create summaries with follow-ups and task assignments

Step 4: Multi-Platform Distribution

Send formatted updates to Slack channels

Update Coda databases with meeting insights

For sales meetings: Create or update HubSpot deal records

Route data to appropriate platforms based on meeting type

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Conclusion:

This workflow consolidates multiple meeting types into one automated system, ensuring consistent documentation and appropriate distribution across your business tools.

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