About Features How it works Docs GitHub Get started
Italiano English
MULTICAM PIPELINE

Test it on your real footage,
not a clean demo

No jargon here — just the path from "I have four camera angles" to "rough cut and exports are ready." Each section answers one real doubt: sync accuracy, AI montage quality, captions, platform exports. One goal: try your first multicam session and see if it works for you.

Multicam sync
2–4 cams
AI montage
Rough cut
Captions
Styled SRT
Platforms
YT·TT·IG·FB
Feature_01

Four angles. Still syncing by hand?

Elena runs a three-camera podcast every week. The bottleneck isn't shooting — it's aligning streams before montage. She used to spend hours in a manual sync tool. Install fear: no weekend Docker project. Sync fear: drift between mics and cameras. Then she dropped all camera files into Shotloom and came back to aligned streams ready for AI montage. Now: ingest after the shoot, pipeline runs locally, rough cut queued. Privacy matters too — unreleased episodes don't leave her machine.

Doubt "Sync won't be accurate"
Proof First session in one evening
Daily gain Drop angles, not manual align
Trust factor Local Docker pipeline
Multicam Sync Flow
Input - podcast_ep03_camA.mp4 - podcast_ep03_camB.mp4 - podcast_ep03_camC.mp4 Sync - Audio alignment across 3 streams - Local processing in Docker - No cloud upload required Output - Aligned streams ready for montage - Progress visible in dashboard
Montage Pipeline States
Stage What happens Dashboard
analyze VAD + face scoring Media tab
montage AI rough cut draft Settings rhythm
captions Styled subtitles Captions tab
export Platform profiles YT·TT·IG·FB
Feature_02

Synced. Still cutting by hand?

Marco covers event multicam and needs TikTok highlights fast. His challenge is montage rhythm under deadline, not shooting. Tools that looked easy in demos became overnight editing marathons. His doubt: can AI montage stay practical or is it a rough draft wall? He kept it when the rhythm clicked: ingest event angles, tweak pace in Settings, return to rough cut and vertical exports. Face-aware 9:16 crop, styled captions, batch from one session. Fewer bottlenecks, no cloud timeline, a weekly process he trusts.

Doubt "AI cut won't be usable"
Proof Tune rhythm in Settings
Daily gain Rough cut before lunch
Trust factor Refine, don't rebuild
Feature_03

Rough cut done. Still exporting one platform at a time?

Luca produces client livestreams with sensitive footage — everything stays on his NAS-backed Docker host. Sara batches lecture multicam for LMS and social. Their doubt: can one session export YouTube 16:9, TikTok 9:16, Instagram Reels, and Facebook without re-ingesting? They tested one full session, checked platform profiles, queued multi-format exports from a single master. That cut the expensive part: re-rendering for every channel. Faster publish cycles, clearer platform coverage, fewer last-minute format fixes.

Doubt "One export per platform?"
Proof YT·TT·IG·FB profiles baked in
Daily gain Batch from one ingest
Trust factor Re-export without re-ingest
Platform Export Queue
From one session - YouTube 16:9 master - TikTok 9:16 (face-aware crop) - Instagram Reels 9:16 - Facebook 16:9 / 9:16 After Settings tweak - Re-export without re-ingesting - Same aligned streams, new profiles

Your first session is what convinces you

Bootstrap tonight, drop 2–4 multicam clips, and see if sync, montage, captions, and exports work for your workflow. If that test passes, you already have a useful routine for tomorrow.