RenameClick

RenameClick is a local-first AI file renamer and organizer for macOS and Windows. It reads supported file contents instead of relying on existing filenames, then suggests clear names and destination folders. In the standard workflow, every suggestion can be reviewed and edited before changes are applied. Undo and redo cover applied renames and moves. Batch processing supports images, documents, text files, and audio recordings. Audio transcription is currently in beta. Organization uses AI Categories, metadata folder presets, or Match Folders, which routes new files into folders that already exist. AI Search finds supported local files by meaning, while Auto Flow watches folders for incoming files and can prepare results for review or use Auto Apply when explicitly enabled.

★★★★★

5.0(1 ratings)

• Local AI. Built-in document and image models, plus the optional audio transcription model, run on the device after a one-time download. Processing does not require sending files to external services when this mode is selected. A model server such as Ollama or LM Studio can be connected by URL. A local server on another computer receives the content. This mode suits confidential data processed inside a controlled environment.
• Cloud providers. RenameClick supports external AI services using the owner's API key. File content is sent to the selected provider, and usage is billed by the provider separately from RenameClick. OpenAI, Google AI, Alibaba Cloud, OpenRouter, Groq, and other OpenAI-compatible APIs are supported. Any service can be added by URL: a model marketplace, a company AI platform, or a private server.
• Batch renaming. The program processes groups of files in one operation. Images, PDF, Office documents, text and structured-text files are supported. Renaming is based on content rather than original filenames. Every suggested name can be edited before applying. Batch mode reduces manual work on large collections and keeps naming consistent.
• AI Categories organization. AI Categories distribute files into semantic groups based on content. The program suggests destination folders together with new names. The user reviews and can change the move route. Categories can be combined with other rules. This helps bring scattered file sets into a single directory structure.
• Metadata folder presets. Folder presets build a directory structure from file metadata. Date, type, or other attributes can define the destination folder. Presets are configured for a specific task. The result is applied together with renaming. This approach simplifies layout for archives, media libraries, and work documents according to predefined rules.
• Match Folders. Match Folders routes new files into folders that already exist in the selected structure. The program compares file content with available directories and chooses a suitable one. If no match is found, the result stays for review. The mode preserves an existing organization and avoids creating duplicate folders. It suits replenishing current archives.
• AI Search. AI Search finds supported local files by meaning, not only by exact name. The query is written in ordinary words. The program analyzes content and returns matching files. Search works with the same file types as renaming. This speeds access to required data in large collections where names do not reflect content.
• Auto Flow. Auto Flow monitors selected folders and reacts to incoming files. Results can be prepared for review before applying. When Auto Apply is explicitly enabled, the program applies changes automatically. The mode suits continuous file streams: scans, downloads, recordings. Settings define which actions run without user involvement.
• Undo and redo. All applied renames and moves can be undone. Redo returns the changes. History covers operations performed within the workflow. This reduces risk during mass processing and allows correcting an erroneous application. Undo and redo work consistently with suggestion review.
• Suggestion review. In the standard mode, every suggested name and destination folder is displayed before applying. The user can edit the name, change the route, or reject the option. Review is available for single files and for batches. This order keeps control over changes and allows aligning the result with accepted naming rules.
• Audio support. The program accepts MP3, WAV, FLAC, M4A, and AAC. Transcription is available for audio recordings in beta mode. Names and categories are formed from the transcript. This applies to meeting records, lectures, interviews, and voice notes. The audio model can be downloaded for local processing or use the selected provider.
• Plans and limits. The Free plan includes unlimited AI analysis and AI Search. It also allows 30 successful applied renames or moves per month. Pro removes the monthly apply limit. The limit concerns applied operations, not analysis. This model allows testing the program before moving to a paid mode.

RenameClick was created by the developer RenameClick. The program was released in 2024 for macOS and Windows. It is written in Swift using Apple platforms and components for on-device AI models. Windows versions use compatible modules for file processing and connection to local and cloud AI services. Development focuses on renaming and organizing files by content rather than by names. Audio transcription support was added in beta mode. Integrations with LM Studio and Ollama expanded the choice of local servers.

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