Doza Assist

Local AI story editor for professional editors that transcribes footage on-device, learns editorial preferences, and exports directly to Final Cut Pro, Premiere Pro, and DaVinci Resolve.

Video Editing

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Doza Assist: AI Video Editing for local documentary and interview story editing on Mac (2026)

Doza Assist is an AI video editing tool by Doza Visuals built for turning interviews and long-form source footage into structured story cuts on a Mac without cloud uploads. Its clearest differentiator is it runs locally on Apple Silicon, keeps footage on-device by default, and exports directly to FCP, Premiere, and Resolve instead of trapping users inside a browser editor.

It is strongest for professional editors and story producers working in Final Cut Pro, Premiere Pro, or DaVinci Resolve who care about privacy and transcript-driven prep. The workflow and pricing are most compelling when the buyer values privacy, editorial prep, and native NLE handoff more than raw manual control.

It is a weaker choice for teams that need Windows teams, browser-first social editors, or buyers who want a broad team collaboration platform.

Doza Assist: Key Specs at a Glance

Feature	Doza Assist
Primary use case	turning interviews and long-form source footage into structured story cuts on a Mac without cloud uploads
Best for	professional editors and story producers working in Final Cut Pro, Premiere Pro, or DaVinci Resolve who care about privacy and transcript-driven prep
Access type	Native Mac app for Apple Silicon
Input types	Interview footage, transcripts, quotes, story segments, and long-form source media
Output formats	Native XML export to Final Cut Pro, Adobe Premiere Pro, and DaVinci Resolve
Output resolution	Not publicly documented
Max video duration	No public per-minute cap is advertised
Generation speed	Runs locally and offline; exact render or analysis times are not publicly documented
Watermark policy	No watermark policy is promoted on the public site
Language support	Transcription input supports 100+ languages, and AI analysis output supports 30 output languages according to the official FAQ
API availability	No public API; optional user-provided cloud model keys are described, but the core workflow is local
Integrations	Final Cut Pro, Adobe Premiere Pro, DaVinci Resolve, and official GitHub distribution for the open core
Collaboration	Not publicly documented
Pricing model	Open-source free core plus one-time paid Pro app
Free plan	Open-source core is free forever under MIT according to the official FAQ
Paid plans	Pro is $199 once, yours forever, with optional $49 per year updates after year one

What Doza Assist Does Well

The privacy story is unusually concrete

Doza Assist does not just say it is private. The site repeatedly states that footage stays on your Mac, works offline, and does not require cloud uploads by default.

The export path respects real editorial tools

Direct export to Final Cut Pro, Premiere Pro, and Resolve is a better fit for professional editors than forcing everything to stay inside a closed AI editor.

The pricing is operationally simple

A one-time $199 Pro purchase is easier to understand than subscription credits when the buyer mainly wants transcript-driven story prep and NLE handoff.

Known Limitations

Doza Assist is built for Apple Silicon Macs, which immediately excludes Windows-centric teams.
Public specs do not document output resolution because the product is more about story prep and NLE handoff than end-to-end finishing exports.
The strongest value is in interviews, transcripts, and story organization, not flashy social-first motion design.
Collaboration and shared review workflow are not a major part of the public product surface.

Best For: Who Should Use Doza Assist

Documentary, interview, and long-form editors who want transcript-aware story building on-device.
Editors who need privacy-sensitive workflows under NDA or client confidentiality.
Mac-based teams cutting in Final Cut Pro, Premiere Pro, or DaVinci Resolve.
Buyers who prefer a one-time purchase over recurring editing subscriptions.

Who Should Look Elsewhere

Choose another tool if you need Windows support today.
Look elsewhere if your top priority is social-first caption styling and instant browser sharing.
Use a broader collaboration platform if many stakeholders need to review and comment inside the same tool.

Pricing and Cost at Scale

Free path: Open-source core is free forever under MIT according to the official FAQ

Paid path: Pro is $199 once, yours forever, with optional $49 per year updates after year one

The free MIT-licensed core makes Doza Assist easy to evaluate without budget approval.

The $199 Pro tier is compelling for editors who will use it regularly, because it avoids the recurring tax common in cloud editing tools.

The optional $49 annual update fee is easier to forecast than usage-based credit burn, especially for teams with steady interview workloads.

Prices can change. Check the official pricing source before budgeting around this tool.

Technical Details and Workflow Notes

Official FAQ says the app is native to Apple Silicon Macs.
Public FAQ confirms support for 100+ transcription languages and 30 AI analysis output languages.
Official site links to the MIT-licensed GitHub repository for the core product.

Getting Started

Test the free core first with a real interview project instead of a tiny synthetic sample.
Validate the transcript quality and story grouping before buying Pro.
Check the XML handoff inside your actual NLE because that is one of the product's biggest claims.
Keep the workflow scoped to story prep and structured selects, where Doza Assist is strongest.

Pro tip: Doza Assist makes the most sense when transcript cleanup and story structure are your bottlenecks, not when final motion polish is the bottleneck.

What Users Are Saying

The external footprint is still small, but the public conversation lines up with the official pitch: local processing, editorial intelligence, and direct NLE export.

What users praise: People respond well to the local-first stance and the promise of story editing without cloud lock-in.

Common frustrations: The footprint is early, so there is not yet a broad base of third-party reporting on long-term stability at scale.