Munch is an AI video repurposing tool that extracts the most engaging clips from long videos and formats them for social platforms.
Munch analyzes long-form video — webinars, podcasts, interviews — and uses engagement modeling to identify the clips most likely to perform on social media. Each extracted clip is automatically reframed to vertical, captioned and annotated with trending post copy and hashtags. The system understands context rather than just cutting on silence, so clips land on coherent moments. Marketers use it to turn one recording into weeks of social content without scrubbing timelines.
Connect or upload your long-form video and let Munch analyze it for high-engagement moments. Review the extracted clips, adjust captions and framing, generate platform-specific post copy and export the batch for scheduling.
Munch offers a free trial; paid plans are tiered by monthly processing minutes, number of exports and brand customization features.
Content marketers, podcasters and social media managers who publish frequently and need to multiply the value of every long-form recording.
Yes, Munch provides a free trial to process a limited amount of footage; ongoing use requires a subscription based on monthly video minutes.
Munch focuses on its web app experience and does not currently publish a self-serve public API for external automation.
Unlike manual editors or basic auto-cut tools, Munch optimizes for virality signals — it chooses what to cut based on predicted engagement, not just silence detection.
Munch is a repurposing tool, not a full editor — clips may need polish before publishing. It pays off most for teams with a steady stream of long-form source material.
Munch accepts uploaded files and links from platforms like YouTube and Zoom recordings, covering webinars, podcasts and interviews. Processing time depends on length and your plan’s monthly minute allowance.
Yes. Auto-generated captions can be corrected and restyled before export, which matters for accuracy on names, jargon and technical terms that speech recognition may mishear.
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