Managing vast libraries of sound effects, music tracks, and voiceover files presents a constant challenge for digital storytellers. Traditional file organization relies heavily on consistent file naming conventions and manual metadata tagging, which frequently break down over long-term production cycles.
Curlo has launched a native macOS application designed to address these library management inefficiencies through the use of on-device artificial intelligence.
The software functions as an audio asset manager that processes files locally on the computer rather than relying on external cloud servers. For video editors, podcasters, and sound designers working under strict non-disclosure agreements or handling sensitive client material, local processing eliminates the security risks associated with uploading proprietary audio to third-party cloud platforms.
According to a recent product feature breakdown by Production Expert, the application utilizes the hardware capabilities of Apple Silicon to maintain rapid search speeds across databases containing tens of thousands of individual audio files.
The core functionality of the new software centers on semantic search capability. Instead of requiring users to remember specific filenames or exact keyword strings, the system allows content creators to locate assets using natural language descriptions. For example, a video producer can type a descriptive phrase like heavy rain on a tin roof or footsteps on gravel, and the underlying AI model analyzes the actual acoustic content of the library to surface relevant matching audio files. This methodology bypasses the limitations of missing or poorly entered text descriptions by analyzing the sound wave itself.
In addition to semantic queries, the application includes traditional metadata search and advanced filtering options. Users can leverage specific commands to filter their libraries by technical parameters, including file format, duration, sample rate, bit depth, and channel count. The platform supports a broad range of standard professional and consumer audio formats, such as WAV, AIFF, FLAC, MP3, CAF, RF64, OGG, and OPUS.
For creators attempting to standardize their archival workflows, the tool incorporates automated Universal Category System classification. The AI can analyze unassigned audio files and automatically batch-assign categories based on a combination of existing embedded text and acoustic characteristics.
Users can also create custom collections to group sounds by specific project, scene, or atmospheric mood without altering the actual folder structure on the physical hard drive.
Advanced features available in the upper tiers include similar audio search, which identifies files that share close acoustic properties with a selected reference track. This assists editors who need to quickly locate slight variations or alternate takes of a specific sound effect during the mixing phase.
The platform also features a local HTTP API, enabling larger production studios to integrate the search engine directly into existing automated pipeline scripts.
The software is structured under a multi-tier pricing model. A free tier allows creators to index up to 5,000 files while utilizing basic semantic search, metadata filtering, and automated category classification.
Upgrading to the professional tier removes the file indexing cap and unlocks metadata writing capabilities, similar audio search, and API access. The application is currently available for download through the Mac App Store.
