Bulk rename files with AI that understands content

Renamer.ai is an AI-powered file renaming tool designed to automatically organize digital files by analyzing their content. It processes documents, images, and other file types to generate descriptive, searchable names based on embedded text, visual elements, or document structure. The tool targets professionals who manage large volumes of unstructured files—including accountants, legal staff, researchers, designers, IT administrators, and marketing teams—where inconsistent naming conventions hinder retrieval, compliance, and collaboration.
Unlike conventional batch renamers that rely on metadata or filename patterns, Renamer.ai uses optical character recognition (OCR) for text-based files and computer vision for images to extract semantic information such as dates, company names, invoice numbers, document types, and subject matter. This enables context-aware naming without manual configuration for each file, reducing reliance on guesswork and improving long-term file discoverability.
Renamer.ai operates in three primary modes: upload-based web processing, desktop application processing, and automated folder monitoring. In the web interface, users upload files up to 100 MB; the system extracts text or visual features, applies configured naming logic, and returns renamed files for download. The desktop app performs the same analysis but processes files locally where possible—only transmitting content for AI analysis before immediate deletion of all processed data.
Magic Folders enable continuous organization: users designate a local or network folder (e.g., Downloads, client dropboxes), select a naming template, and activate monitoring. As new files arrive, Renamer.ai analyzes them in real time and applies the chosen naming convention without user intervention. Users can preview suggested names before applying changes and adjust templates to include variables such as document type, date, project name, or custom context fields.
The renaming engine supports multilingual input and adapts to domain-specific terminology—for example, extracting vendor names and amounts from invoices, identifying meeting participants and dates from notes, or describing image content for photos. All processing is purpose-limited to filename generation; no data is retained or used for model training.
Renamer.ai addresses common document management challenges across industries. Accounting teams use it to standardize invoice and contract naming, enabling rapid retrieval during audits or tax preparation. Legal departments apply it to legacy case files with inconsistent naming, reorganizing tens of thousands of documents by case ID, jurisdiction, and filing date. Research institutions leverage multilingual support to process international academic papers and datasets, while marketing and design teams automate asset organization using project-based naming conventions.
Additional applications include HR document management (employee files, onboarding packets), SEO optimization of image filenames, paperless office transitions, and regulatory compliance workflows requiring traceable, auditable naming. The tool reduces manual file handling time, prevents duplicates through consistent naming, improves search accuracy across local and cloud storage, and supports scalable, repeatable organizational policies without requiring technical expertise.
| Plan | Monthly Files | Price (Billed Annually) | Key Features |
|---|---|---|---|
| Starter | 15 | $0 | Desktop app, batch rename, Magic Folders, normal support |
| Pro | 200 | $9.95 | Enhanced AI renaming, priority template access, normal support |
| Power User | 1,000 | $29.95 | Advanced AI models, priority support, custom context fields |
| Ultimate | 5,000 | $99.95 | Highest-tier AI, dedicated support, enterprise-grade SLA |
All plans include cross-platform desktop apps (Windows/macOS), batch renaming, Magic Folders, and template customization. Custom enterprise plans are available for organizations requiring higher volume, on-premises deployment, or integration support.