Why on-device AI
Three sentences that explain why SwiftyClip exists.
The cloud AI clippers — Opus Clip, Submagic, Vugola, Klap — have a shared architectural flaw: every minute of source video you feed them costs them real money in GPU time. They amortize that cost by metering credits and throttling you.
Your Mac already has the hardware.
An M2 Pro's Neural Engine runs Whisper at 2.2% word error rate on 0.3 watts. The Vision framework detects faces in 4K video at real-time frame rates. MLX runs Qwen 2.5 quantized for hook-detection scoring. Nothing in the transcribe → analyze → score → render pipeline needs a cloud GPU in 2026.
So the marginal cost is zero.
SwiftyClip doesn't pay per clip. Which means you don't pay per clip. Unlimited minutes are included in the $9 Starter tier. Unlimited minutes are included in the $149 Lifetime. No "your credits have run out" emails. No "video is still processing" banners. No queue behind 50,000 other users hitting the same GPU cluster during a Black Friday content push.
And your video never leaves the Mac.
The cloud clippers' terms of service routinely grant them broad rights over uploaded content. Unreleased podcast episodes with celebrity guests. Closed-door interviews under NDA. Premium course content you're about to launch. All of it sits on someone else's storage layer, indexed by their ML training pipeline, for an indefinite retention window.
SwiftyClip's sandbox entitlements, shipped with every build, don't include any network-upload capability for video files. The only outbound traffic from the app is your Stripe subscription status and (optionally) the final clip when you explicitly schedule a post.