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YouTube Transcript Scraper for AI & RAG

Turn any YouTube video into clean, structured text ready for LLM context windows, RAG pipelines, or full-text search. Extracts captions directly from YouTube's internal player data — no browser, no API key, no rate-limit headaches. Process hundreds of videos in parallel with configurable concurrency.

Features

• Full transcript extraction — pulls the complete caption track from any video with available subtitles
• Timed segments — returns individual segments with offset and duration for precise referencing
• Bulk processing — extract transcripts from hundreds of videos in a single run
• Parallel execution — configurable concurrency to balance speed and reliability
• AI-ready output — concatenated plain text field perfect for LLM ingestion
• No API key required — works directly with YouTube's public caption data

Input

Input Example

{
"urls":[
"https://www.youtube.com/watch?v=dQw4w9WgXcQ",
"https://www.youtube.com/watch?v=jNQXAC9IVRw"
],
"concurrency":10
}

Output

Each video produces one dataset row containing the full transcript as a single text block, plus an array of timed segments for granular access.

Key output fields:

Output Example

{
"inputUrl":"https://www.youtube.com/watch?v=jNQXAC9IVRw",
"videoId":"jNQXAC9IVRw",
"fullText":"Welcome to the presentation. Today we will cover three key topics in machine learning. First, let us look at supervised learning and how it differs from unsupervised approaches...",
"segments":[
{"text":"Welcome to the presentation.","offset":0,"duration":2400},
{"text":"Today we will cover three key topics","offset":2400,"duration":3100},
{"text":"in machine learning.","offset":5500,"duration":1800}
]
}

Pricing

Pay per event on Apify platform.

Use Cases

• RAG pipelines — feed video transcripts into vector databases for retrieval-augmented generation
• Content repurposing — convert video content into blog posts, summaries, or social media threads
• Research analysis — make lecture and conference talk content searchable and quotable
• SEO audits — analyze what competitors say in their videos without watching them
• Training data — build domain-specific datasets from educational YouTube content

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