Zush is an AI file renamer for Mac that processes screenshots, PDFs, photos, videos, audio, and documents. It analyzes file content and generates descriptive names in batches, supporting over 100 formats, folder monitoring in the background, custom templates, Finder tags, keyboard shortcuts, and private offline mode with Ollama or BYOK.
Download Zush (Official links)File size: 83.7 MB
The latest version of Zush is: 3.8.3
Operating system: Windows, MacOS
Languages: English, Japanese, German, French, Portuguese, Spanish, Italian, Korean, Chinese
Price: $0.00 USD
- Smart batch rename. Processes mixed folders with content analysis across more than 100 file formats, including images, design files, PDFs, audio, video, iWork, and Office documents. The system examines each element and proposes a name based on what it actually contains rather than superficial metadata.
- Folder monitoring. Watches one or multiple folders continuously. Zush runs in the background and processes new files automatically as they appear, applying configured renaming rules without manual intervention.
- Custom AI prompts. Allows modification of renaming and tagging behavior through personal instructions. The user defines specific criteria for style, length, date inclusion, project names, or any parameter relevant to the workflow.
- Templates and naming blocks. Includes ready-made templates for screenshots, designers, photographers, video, music, bookkeeping, legal documents, clinics, and other sectors. It also provides a visual block editor with over 70 fields across file, media, audio, EXIF, finance, work, design, and travel.
- Finder tags and metadata. Applies Finder tags and associated metadata automatically during renaming. This maintains visual classification and order within the macOS file system.
- Quick rename shortcut. Allows renaming selected files directly from Finder with a keyboard combination, speeding up the task without opening the main application window.
- Names in over 60 languages. Generates file names in more than 60 languages with customizable date formats, adapting to regional conventions and the needs of international teams.
- Activity statistics. Shows activity over time, file type breakdown, rename streaks, and time saved. The data allows evaluation of processed work volume and adjustment of rules to optimize results.
- Offline AI mode. Runs private local models through Ollama so that file analysis does not leave the machine. Documents, images, audio, and video are processed locally without sending data to external servers.
- BYOK (bring your own key). Allows connecting AI provider keys from the user's own account to perform cloud renames. Control over cost, model, and privacy remains with each individual account.
- RAW format support. Recognizes RAW files from Canon CR2/CR3, Nikon NEF, Sony ARW/SR2, Adobe DNG, Olympus ORF, Fujifilm RAF, Panasonic RW2, Pentax PEF, Samsung SRW, and others. It analyzes the visual content of these captures to produce descriptive names.
- Audio and voice analysis. Processes MP3, M4A, WAV, FLAC, OGG, WebM, and MPGA with music recognition, audio profiling, and speech analysis. It extracts short snippets or relevant features to generate names consistent with the sound content.
- Documents and spreadsheets. Works with TXT, MD, JSON, XML, YAML, EML, CSV, TSV, RTF, DOC, DOCX, XLS, XLSX, PPT, PPTX, ODT, ODS, ODP, Pages, Numbers, Keynote, SRT, and VTT. It extracts text or a compact summary for name generation without storing the information on servers.
- Design files. Supports Sketch, Figma, Adobe Illustrator, and Adobe Photoshop exports. It reviews layers, texts, and composition to suggest names that reflect the purpose of the design.
- Video formats. Covers MP4, MOV, M4V, MPEG/MPG, 3GP, DV, TS, MTS, M2TS, and VOB. It analyzes representative frames and associated audio tracks to identify scenes, places, or events.
Zush was created by an independent team focused on productivity tools for macOS. The first version appeared in 2024 after a testing period with users working with large volumes of screenshots and multimedia files. Development continues with periodic updates that expand format support and refine analysis models. The application is written in Swift and uses native Apple frameworks for file processing, Finder integration, and background task management.
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