Hey everyone!
Three major features just landed in OpenCut AI and they all run locally on your machine.
1. AI Co-Pilot Agent

This is the big one. Tell the editor what you want in plain English and it creates a step-by-step plan, then executes it.

Examples:

- "Make this a 60-second vertical reel with captions and trending music"

Hey everyone!
Big update just shipped v0.4.0, our largest release yet. Six new AI features, and every one of them runs locally. Your footage still never leaves your machine.
What's new
- AI dubbing, fully local a new NLLB-200 translation service batch-translates transcripts on-device (Whisper translate voice clone render). Optional Sarvam fallback only for Indian language pairs, if you configure it.
- Video background removal per-frame matting with the result dropped in as a non-destructive alpha layer above your clip. Original stays untouched.
- Auto B-roll from your own footage on-device CLIP search matches each transcript segment to clips you already have and inserts the best match. No stock libraries, no uploads.
- Multilingual captions one-click translation into multiple languages with per-track SRT/VTT export.
- Edit by speaker diarization labels who spoke when; remove, tighten, or isolate a single speaker's segments like text.
- Automatic multicam sync client-side audio cross-correlation aligns camera angles without timecode. Preview offsets with confidence scores, apply in one undoable step.
Also in this release
- Visual footage search powered by local CLIP embeddings (shipped earlier this spring)
- Thumbnail A/B testing and YouTube virality scoring
- New model support: Sarvam AI, Smallest AI, Kimi K2, Google Gemma
- Hardened upload endpoints, stabilized VPS deployment, and a repaired build/CI pipeline community contributions from @MikyJ05 and @interfluve-wav landed in this release. Open source works.
Why it matters
Every other "AI video editor" asks you to upload raw footage to the cloud. For unreleased material, client work, or anything sensitive, that's a non-starter. We keep wrapping more intelligence around the editor while keeping the architecture boring and private: Docker services on your own hardware, no telemetry, no account required.
Full changelog: /changelog/0.4.0 on the site.
What should we build next and what would you dub first?

Hey everyone! Excited to share what we've been working on.
We just added Virality Score to OpenCut AI, a neuroscience-backed engagement analyzer that grades your video A-F across 7 signals before you hit publish.
How it works
Drop a video into the editor, click "Check Virality Score," and get:
- Hook Strength does your first 1.5s grab attention? (33% of TikTok viewers scroll past in 3 seconds)
- Curiosity Gap is there unresolved tension keeping viewers watching?
- Audio Energy are your levels and pacing right for the platform?
- Beat Sync do visual cuts land on audio beats?
- Face Presence the #1 short-form retention driver
- Emotional Arc does your clip build to a payoff or flatline?
- Viral Potential LLM-powered composite prediction
Each signal scores 0-100, rolls into a letter grade, and comes with actionable suggestions ranked by expected impact.
Why we built this
Most creators publish and pray. The difference between 10 views and 100K views is rarely the content it's the presentation. We used neuroscience research (dopamine prediction loops, orienting response, information-as-reward) to identify what actually holds attention, then built scoring algorithms around real platform data:
- 65% of 3-second viewers watch 10+ seconds
- Text overlays increase view time by 28%
- Videos with 65%+ 3-second retention get 4-7x more impressions

Also in this update: YouTube to Reels
Paste a YouTube URL and OpenCutAI will auto-detect the best 15-90s clips, score each one, reframe to 9:16 with face tracking, add captions, and export ready-to-upload reels. The full pipeline runs locally.
Would love to hear from creators, what signals would you add to the scoring? What's the first thing you'd test this on?

Hey everyone!
We just shipped the biggest update to OpenCut AI since launch, turning it from an AI-powered text editor into a full professional video editor. All open source, all self-hosted.
Here's what's new:
AI Features
- AI Music Generation Pick a genre (15 options), mood (12 options), and tempo. Generate royalty-free background music and drop it on the timeline.
- AI Thumbnail Generator Describe what you want or let AI generate from your transcript. 5 styles, 4 platform sizes, up to 4 variations at once.
- AI Script-to-Video Write a script, AI generates voiceover, creates visuals, and builds the timeline automatically.
- AI Auto-Duck Automatically lowers background music when speech is detected. Configurable duck amount and fade curves.
- AI Auto-Color Correction 8 one-click profiles: Vibrant Pop, Film Look, Warm Sunset, Cool Blue, and more. Batch apply to all clips.
- AI Video-to-Shorts One click to auto-select the best clip, trim to target duration, set 9:16/1:1/4:5 canvas, add subtitles.
-Speaker-Labeled Captions Color-coded speaker labels, rename speakers, apply captions with speaker awareness.
Professional Editor
- 20 transitions Iris Wipe, Clock Wipe, Morph, Glitch, Film Burn, Page Peel, Cube Spin, and more. All WebGL shaders.
- 12 effects + 22 filter presets Sharpen, Chromatic Aberration, Film Grain, Motion Blur, Duotone. Presets: Sunset Glow, Cyberpunk, Film Noir, Retro VHS.
- Crop & Mask Rectangle, ellipse, polygon masks with feather and inversion.
- Multicam Editing Sync angles, switch views with one click.
- Marker System Colored markers with notes, jump between markers.
- J/K/L Shuttle Playback Variable speed reverse and forward (1x-8x).
- Ripple Trim Delete clips and close gaps automatically.
- Compound Clips Nest multiple clips into one, un-nest anytime.
Audio
- Audio Effects Chain Per-track EQ, Compressor, Noise Gate, Reverb, De-esser, Limiter with Web Audio API processing.
- Direct Recording Record audio from your mic directly to the timeline with live level metering.
- LUFS Normalization Measure loudness and normalize to platform targets (YouTube, Spotify, Apple Podcasts, broadcast standards).
- Beat Detection Detect BPM, visualize beats, snap edits to the beat grid.
Workflow
- Batch Export Queue up to 8 platform presets (YouTube 1080p/4K, TikTok 9:16, Instagram, Twitter, Podcast Audio).
- Keyboard Shortcut Editor Full management UI with search, rebind, conflict detection.
- Undo History Panel Visual command history, click to jump to any point.
- Color-Coded Tracks 8 track colors + track locking.
- Filmstrip Thumbnails Cached frame thumbnails on timeline clips.
- Template Gallery 8 project templates (YouTube Intro, TikTok Vlog, Podcast Highlight, etc.).
- Share via Link Generate share links with expiration and password protection.
Why this matters
Every other AI video editor (Descript, CapCut, Runway) sends your footage to the cloud. OpenCut AI runs entirely on your machine. No subscriptions, no data leaving your server, no per-seat pricing.
Self-host on a $20/mo server or run it locally on your laptop or desktop. MIT licensed.
What feature would you want us to build next?

Hey everyone!

We just shipped an AI Video Generation hub directly into OpenCutAI. Generate video from a text prompt, preview it, and drop it on your timeline all from one panel. No switching between browser tabs.

What's supported:

- 9 models across 5 providers Runway Gen-3 Alpha, Pika 1.0, Kling v1.6 Pro, MiniMax Video-01, Stable Video Diffusion, Seedance 2.0, Stable Video XT, Luma Dream Machine, and CogVideoX (local, free, no API key)

Hey Product Hunt

OpenCut AI the privacy-first, open-source AI video editor.

The problem

Every major AI video editor (Descript, CapCut, Runway) makes you upload your raw footage to the cloud. For journalists, enterprises, and anyone who cares about privacy, that's a dealbreaker.

Hey Product Hunt!

We just shipped Visual Search in OpenCut AI the privacy-first, open-source AI video editor.

Ever scrubbed through 200 clips hunting for "that outdoor shot with someone talking"?

Now you just type it.

Hey everyone

We built OpenCut AI because we were tired of video editors that phone home. CapCut sends data to ByteDance. Descript uploads everything to AWS. Runway is cloud-only and credits-based. We wanted an editor that stays on your hardware.

Here's what you get:

AI that runs locally:

Hey everyone!
Just shipped A/B testing for thumbnails and hooks directly into OpenCut AI. Generate variants, score them automatically, and pick the winner all inside the editor, no external tools needed.
Thumbnail A/B Testing
Generate up to 4 thumbnail variants, then auto-score each one on:
- Contrast
- Text readability
- Face presence
- Color vibrancy
- Composition
Each variant gets a letter grade (A-F) and an overall score. The winner gets a "Recommended" badge. You can also score thumbnails you've already generated.
Hook A/B Testing
Got a transcript? Generate 5 hook variants different openings designed to grab attention in the first 3 seconds. Each variant gets an estimated engagement score so you can compare them side by side.
Analytics Dashboard
Tracks your scoring history over time:
- Average composite score
- Grade distribution
- Per-signal breakdown (hook, curiosity, energy, etc.)
- Strongest and weakest signals
- Score trend chart
Why this matters
TubeBuddy puts A/B testing behind their $15/mo Legend plan. VidIQ does the same. We think this should be free and built into your editor not a separate subscription.
Everything runs locally. No data sent to third parties. MIT licensed.
What other YouTube optimization features would you want built in?

Hey everyone!
We just shipped TurboQuant into OpenCut AI, and this one changes what hardware you need to run the full AI stack.
The problem we had
OpenCut AI runs everything locally -- LLM, transcription, voice cloning, image generation. That's great for privacy, but brutal on memory. Running the full stack needed 35+ GB RAM. Most of our users have 8-16 GB laptops, so they were stuck with tiny 1B models that gave mediocre scripts, slow commands, and limited context.
What TurboQuant does
TurboQuant implements two algorithms from Google Research paper PolarQuant and QJL. That compress the KV cache (the biggest memory bottleneck during AI inference) by up to 6x with mathematically proven quality preservation.
In plain terms: your AI models now use a fraction of the memory without getting dumber.
Before vs After
On a 16 GB machine:
- Before: Llama 3.2 1B + Whisper Base + TTS = barely fits, mediocre quality
- After: Llama 3.1 8B + Whisper Medium + TTS = runs comfortably, dramatically better output
On an 8 GB machine:
- Before: Could only run the 1B model alone
- After: Runs a 3B model + Whisper Base + TTS together
Full stack memory:
- Before: 35 GB for everything
- After: 15 GB for everything
What this means for editing
- Better AI commands "remove the intro" actually works now because Mistral 7B understands context far better than a 1B model
- Better transcription Whisper Medium fits where only Whisper Base could before, so captions are more accurate
- Longer content: Process hour-long podcast transcripts without running out of memory. The 6x KV cache reduction means 6x longer input context
One-click setup in Settings
We added a new AI Optimization panel in Settings. It auto-detects your hardware and recommends the best configuration:
- Performance Tier: Lite (4-8 GB), Standard (8-16 GB), or Pro (16-32 GB). Each tier is tagged with "Best for your hardware" based on your actual RAM.
- KV Cache Compression: Pick 4-bit (near-lossless), 3-bit (5x compression), or 2-bit (aggressive). Recommended level highlighted based on your system.
- Memory Budget: Set once, and the system optimizes everything to fit.

Would love to hear, what's your RAM situation, and does this make local AI editing viable for you?