macOS video editor Apple Silicon Software asset for acquisition
A native Mac video editor with on-device transcription, voiceover, auto-editing and image generation. No cloud APIs, no accounts, no telemetry.
Packaged app v0.1.0 63 automated tests Zero running costs
Network log · 0 requests
0Zero running costs. No servers, no cloud AI APIs, no per-user bills — everything runs on the user’s Mac.
See what’s includedPopular consumer editors send speech, voice and generation jobs to their servers, behind sign-ins and credits. Kadr Studio does that work on the user’s own machine.
Media library, multitrack timeline, live preview, inspector and AI panel — in one window.
Every screenshot on this page is the real app. The interface ships in English and Russian: it follows the system language and switches in the app (top bar or View → Language) without a restart.
Thumbnails, duration, resolution, fps and size for every import.
Live preview with frame-accurate timecode; a 16:9 / 9:16 / 1:1 switch in the top bar.
Transform, speed, volume, fades, colour and transitions per clip.
Video, audio, text and subtitle tracks with snapping, markers and 200-step undo.
60 unedited seconds of the packaged app on an M4, in its English interface: playback, a split and undo, an image generated on-device, and Auto Reframe to 9:16 and back. One continuous take, no network.
Screen recording of the packaged app Apple M4, 16 GB all AI ran locally no audio or cursor
Video, audio, text and subtitle tracks with the tools editors expect. A 99-clip, 4-track project stays at 60 fps.
The playhead moves to 4 seconds, S splits the aerial coast clip in two, Q trims one second from the head of the left part, and the AI voiceover clip snaps to the playhead.
Split 13–15 ms on 99 clips60 fps playback200-step undoSnappingMute / lock / hide
Transcribe locally, get a caption track, fix any word, export SRT, VTT or TXT — or import an existing SRT.
As the playhead crosses each speech peak, the next word of the subtitle appears, ending with the full line: Everything runs on this Mac, even offline.
Transcript · auto-generated, editable
Language
Export
Font, weight, colour, background, outline, shadow and position — set once and applied to every subtitle on the track, then burned in on export. Titles get the same controls plus five presets.
Roadmap: word-level captions
Ten on-device features behind nine provider interfaces. Partial features are labelled — never hidden.
Transcription language in the app: Auto, Russian or English.
A speech waveform is converted into a row of transcribed words.
Transcribes locally with voice-activity filtering to suppress phantom phrases, then builds an editable caption track.
4–6× realtime
Animations are illustrative; the captures beside them are the real app timings: Apple M4, 16 GB RAM
The demo teaser in 16:9, reframed to 9:16 and to 1:1 by Auto Reframe — face-aware where it finds a face, centred where it doesn’t.
Real app captures, preview area demo project made with the app’s own AI
The Model Manager installs optional models only when the user asks, shows size, RAM, licence and commercial terms for each, and marks what is built in. Nothing downloads automatically. Listed download sizes are 0.2–3.6 GB per model — about 8.5 GB for every model this page describes.
“Used: 18.0 GB” in the capture is the test Mac’s disk: about 15 GB for this page’s models as installed, plus two Whisper variants the demo does not use.
Heavy sources play from lightweight proxies automatically. Exports always use the originals.
A 6-second 4K60 HDR original gets a 720p proxy with GPU tone-mapping in about 6.5 seconds on an Apple M4; editing plays the proxy at 60 fps; export renders from the original.
4K, HEVC, HDR and ProRes get 720p edit proxies HDR is tone-mapped to SDR (macOS) no HDR export
FIG 09 Real app the 20 s demo timeline exported in 3.8 s
Autosave within 1.5 seconds of every change, atomic writes and an automatic backup copy.
Network access is blocked at three layers, and every request is logged where the user can see it. The only traffic is a model download the user explicitly starts.
Illustrative · the enforcement layers, summarised
Illustrative summary: the interface, the main process and both AI workers are offline, the full workflow runs, and the network request count stays at zero.
Verified end to endA test runs the whole workflow with networking denied at the OS kernel level. The dialog on the left is what the app reported after generating the images, video, voiceover and subtitles used on this page.
Six more full captures from the running app, each with English notes on what it shows.
FR 01/06
A sandboxed Electron shell, a pure TypeScript editing core, an LGPL FFmpeg build and out-of-process AI workers — each layer replaceable.
FFmpeg, whisper.cpp and Python workers run as child processes. The UI stays at 60 fps during export, proxies and AI jobs.
Nine typed provider interfaces. Replacing a model means replacing a provider; preview and export share one frame model.
Auto Cut, highlights, reframing and silence cuts are unit-tested functions that propose a change.
A bundled, relocatable Python 3.12 with two isolated AI environments. The user installs nothing.
The benchmarks below come from recorded runs on an Apple M4 with 16 GB RAM (04.10.2026). Per-feature AI timings elsewhere on the page are stated measurements on the same machine.
Export · 3:06 timeline → 1080p
28.6s
6.5× realtime · 99 clips · 4 tracks
bar = render time vs. timeline length · Recorded run 04.10.2026
UI during playback, export, proxies
60fps
p95 frame time 18 ms
bar = 60 fps target · Recorded run 04.10.2026
Split on a 99-clip project
13ms
13–15 ms measured
bar = one frame at 60 fps (16.7 ms) · Recorded run 04.10.2026
Memory, all processes
<900MB
845 MB source · 889 MB installed app
bar = share of 16 GB · Recorded run 04.10.2026
Automated tests
63
48 unit/integration · 7 worker · 8 e2e
run 06.10.2026 · longest model test run on its own · Recorded run 04.10.2026
All green on 04.10.2026 — from source and against the installed app with every development dependency hidden.
19 issues found and fixed during verification and packaging (11 in QA, 8 in packaging) — documented in the technical package.
| Partial + roadmap | Status | Note |
|---|---|---|
| Scene detection + highlights | Partial | Cut-mapping defect (quick fix); highlights are markers |
| Auto Cut proposals | Partial | Silence rules; scene rules wait on scene fix |
| Auto Reframe | Partial | Beta: one framing per clip |
| Audio clean-up | Partial | Denoise is DSP, not neural |
| Colour + speed | Partial | Basic: no curves/LUTs, constant speed |
| Video generation | Partial | Experimental: 512×288, 2–3 s, 16 GB |
| HDR sources | Partial | Tone-mapped to SDR, macOS |
| Voice cloning | Partial | Engine only, no UI |
| Windows | Partial | Platform layer prepared, not yet run on Windows |
| Keyframes + animations | Roadmap | Unlocks continuous reframe |
| Word-level captions + transcript editing | Roadmap | Whisper segments exist |
| Masks, chroma key, stabilization | Roadmap | Opportunity |
A working product today, and the cheapest next steps to take it further. Opportunities, not commitments.
Also: a portable editing core with no OS dependencies and a build that bundles its own runtime. The exact list of deliverables is confirmed during due diligence.
Directions an acquirer could take
Sell a one-time licence or a subscription: with no per-user cloud cost, margin does not shrink as usage grows.
Media that cannot leave the building — offline is already enforced and tested end to end.
Keep the core local and free; offer larger models as downloads through the existing Model Manager.
Lift the editing core, proxy pipeline or local-AI workers into your own app; every layer is replaceable.
Straight answers, including the parts that are not finished.
The full source code (TypeScript/React/Electron app, Python AI workers, build and packaging scripts), the automated test suites and fixtures, the reproducible macOS build pipeline producing a self-contained .app and .dmg, project documentation (architecture, feature status, build guide, licence audit, release checklist) and brand assets (name, app icon). Exact deliverables are confirmed during due diligence.
macOS 13+ on Apple Silicon (M1–M4), verified on an M4 with 16 GB RAM. Intel Macs are not supported. Windows is partial: the platform layer is prepared but the app has not yet been run on Windows.
No. There are no cloud AI APIs, accounts or telemetry. The only network use is an optional, user-initiated model download, which is logged in the app. After models are installed, the entire workflow runs offline — verified by an automated test with networking blocked at the OS level.
Whisper, Silero VAD, Chatterbox, RUAccent and YuNet are MIT; U²-Net is Apache-2.0. Stable Diffusion 1.5 and AnimateDiff-Lightning use CreativeML OpenRAIL-M (LCM-LoRA: OpenRAIL++): commercial use is permitted, with use-based restrictions that must be passed on to end users in the EULA. Non-commercial models were deliberately excluded. A full audit is part of the package.
Yes, and they are documented: bundling consolidated licence texts, publishing or offering the exact FFmpeg/libvpx sources for the LGPL build, carrying OpenRAIL restrictions into the EULA, and keeping AI-content labelling (implemented) and the TTS watermark. H.264/AAC encoding uses OS codecs; patent questions should be reviewed by counsel before launch.
It is ad-hoc signed. It is not signed with an Apple Developer ID and not notarized, so a downloaded DMG triggers a Gatekeeper warning. The build documentation lists the entitlements and steps needed to sign and notarize with a Developer ID certificate.
Partial — prepared, not proven. Paths, executables, process handling, Windows hardware encoders and system TTS are implemented in a single platform module, and a setup script exists — but the app has not been run on Windows. HDR-to-SDR conversion and GPU-accelerated generation on Windows are not done.
English and Russian. By default the app follows the system language (Russian on Russian-language systems, English otherwise), and the language can be switched at any time from the top bar or View → Language, without a restart. The interface, native menus and dialogs, job and error messages, numbers, dates and units are localized through typed dictionaries, so adding a language is mainly a matter of a new dictionary file. Transcription supports automatic language detection (the app offers Auto, Russian and English), and neural voiceover supports nine languages.
AI features sit behind typed provider interfaces, so swapping or adding a model does not touch the UI or timeline. Transitions live in a registry evaluated identically by preview and export. OS differences are isolated in one platform module. The editing core is pure, OS-independent TypeScript covered by unit tests.
Partial: scene detection (a UI mapping step drops the cuts FFmpeg finds — an isolated fix), Auto Cut (silence rules work; scene-length rules wait on that fix), Auto Reframe (one framing per clip), highlights (markers only), audio denoise (DSP), colour and speed (basic), video generation (experimental), HDR (converted to SDR), voice cloning (engine only) and Windows (not yet run). Roadmap: keyframes and animations, word-level captions, transcript editing, masks, chroma key and stabilization. The full list is in the status matrix above.
An Apple Silicon Mac with macOS 13+, 8 GB RAM for editing, transcription and voiceover; 16 GB for video generation. About 3 GB for the app, plus optional models listed at 0.2–3.6 GB each (about 8.5 GB of downloads for every model on this page; installed on the test Mac they take about 15 GB on disk).
None built in. There is no backend, no cloud AI API and no account system, so there are no servers or per-user fees to pay. Distribution costs, such as an Apple Developer Program membership and hosting the installer, are up to the new owner.
This site presents the product and its codebase; there is no price on it. Price, transfer terms, commercial history and the exact list of deliverables are covered in the marketplace listing where this showcase is published, and inquiries go through that listing.
A packaged, tested macOS video editor whose AI runs entirely on the Mac — offered as a complete software asset.
Inquiries, price and transfer terms are handled through the marketplace listing where this showcase is published.
