AI Video Summarizer - Summary, Key Points and Chapters
Turn a video or audio file into a summary, key points, chapter markers and SEO copy
Upload your video or audio
Drag and drop or click to select
Video .mp4, .avi, .mov, .mkv or audio .mp3, .wav, .m4a, .aac (up to 100 MB)
How It Works
Upload Video or Audio
Drop in an mp4, a podcast mp3, or any recording. Both work.
Let the AI Read It
We transcribe it if needed, then read the whole transcript, not just the opening.
Copy or Download
Take the summary, key points, chapters and SEO copy as TXT, Markdown or JSON.
Why Use Our Summarize Tool
Handles Long Recordings
A two hour podcast is summarized section by section, so nothing past the first few minutes is quietly ignored.
Real Chapter Timestamps
Chapter markers snap to actual transcript boundaries. Invented timestamps are discarded rather than shipped.
Ready to Paste
Chapters export as plain 00:00 lines that YouTube turns into clickable links.
Choose Your Plan
Start free. Upgrade when you need more.
Guest
$0
no signup
- 100MB uploads
- 3 tasks/day
- Watermark
- Standard speed
Hourly Pass
$1.99
per hour
- 2GB uploads
- Unlimited/1hr
- No watermark
- 5x speed
Pro
$12.99
/month
- 10GB uploads
- Unlimited tasks
- No watermark
- 5x speed
What Creators Say
“I paste the chapters straight into the YouTube description box. It saves me twenty minutes an episode.”
Dana R.
Podcaster
“Used it on a 90 minute webinar recording and got a summary I could send to the team the same afternoon.”
Marcus L.
Product Marketing
Frequently Asked Questions
Does it work on audio files?
Yes. Podcasts, interviews and voice memos all work. The only difference is chapter markers, which are video only because there is no picture to seek to in an audio file.
Do I need to transcribe the file first?
No. If the file has no transcript we create one automatically, and it is saved so the other tools can reuse it.
How long can the recording be?
There is no fixed limit. Long recordings are split into sections at natural pauses, summarized separately, then condensed into one summary.
Are the chapter timestamps accurate?
Every timestamp is snapped onto a real transcript boundary. If the model proposes a time that matches no speech, that chapter is dropped rather than pointing you at the wrong moment.