Curlo

Product Introduction

1. Definition: Curlo is a macOS-native audio asset management (AAM) application, a technical tool for cataloging, searching, previewing, and editing audio files and their metadata. It leverages on-device machine learning (ML) to provide semantic search capabilities.
2. Core Value Proposition: It exists to solve the problem of managing large, disorganized sound effect (SFX) and music libraries by enabling users to find sounds using natural language descriptions, all while maintaining complete data privacy through 100% local processing on Apple Silicon Macs.

Main Features

1. Semantic & Metadata Search: This feature allows users to search their audio library using conversational queries like "car engine starting" or "tense ambient drone." It works by using local AI models to generate vector embeddings from the acoustic content of audio files, which are then matched against the vector representation of the text query. This is complemented by slash-command syntax (e.g., /tag footsteps, /ucs 01.01.01, /format WAV) for precise, traditional metadata filtering.
2. Similar Audio Discovery: Users can select any audio file or a specific time region within a waveform to find sonically similar sounds across their entire library. This works by comparing the AI-generated acoustic fingerprint (embedding) of the selected audio segment against the embeddings of all other indexed files, identifying matches based on timbral, textural, or harmonic similarity rather than metadata.
3. AI Auto-Tagging & UCS Support: Curlo can automatically analyze uncategorized audio files and suggest or batch-assign relevant tags and Universal Category System (UCS) codes. This works by combining analysis of existing file metadata (ID3, BWF chunks) with the acoustic analysis from its local AI models to infer logical categories, streamlining the organization of legacy or unlabeled libraries.
4. Fluid DAW Integration & Clip Extraction: The application includes a professional, zoomable waveform viewer for precise previewing. Users can highlight a specific clip region and drag it directly as an audio file into Digital Audio Workstations (DAWs) like Logic Pro, Pro Tools, or video editors like Premiere Pro. It also allows for instant bouncing of selected clips to folders or virtual collections without moving the original files.
5. Local Developer API: Curlo exposes a localhost HTTP API, allowing power users and studios to integrate its search, tagging, and management functions into custom automation scripts, pipeline tools, or other software, enabling programmatic control over the audio library.

Problems Solved

1. Pain Point: The inefficiency and inaccuracy of managing massive sound libraries using only filenames, folder structures, and manual tagging. Traditional methods fail when users cannot remember a specific filename or when files are poorly tagged.
2. Target Audience: Professional sound designers, audio post-production engineers, film and video editors, game audio developers, podcast producers, and short-form content creators (e.g., short drama creators) who work with extensive libraries of SFX and music on macOS.
3. Use Cases: A video editor needs a specific "door creak" sound but only has generic filenames; they can search semantically. A sound designer wants to find all "metallic impacts" with a certain reverberant quality for a scene. A post-production studio needs to standardize and tag a legacy library of 50,000 SFX with UCS codes automatically.

Unique Advantages

1. Differentiation: Unlike cloud-based semantic search tools (which upload data) or traditional file managers (like Soundminer, Basehead, or even Finder), Curlo offers AI-powered search with a strict privacy-first, fully local architecture. It runs optimized Core ML models directly on the Mac's Neural Engine, ensuring no audio data or search queries leave the device.
2. Key Innovation: The integration of a high-performance, on-device AI inference pipeline for audio understanding, specifically optimized for Apple Silicon (M-series chips). This allows for complex semantic and similarity searches to be executed locally with low latency, even on libraries with tens of thousands of files, which is a significant technical achievement for a desktop audio application.

Frequently Asked Questions (FAQ)

1. Does Curlo work without an internet connection? Yes, Curlo's core AI search, tagging, and library management features are fully functional offline. All processing occurs locally on your Mac, and no internet connection is required after installation.
2. What audio formats does Curlo support? Curlo supports a wide range of professional and consumer audio formats including WAV, AIFF, FLAC, MP3, CAF, RF64, OGG, and OPUS, ensuring compatibility with most sound library collections.
3. Can Curlo edit the metadata inside my original audio files? Yes, Curlo includes a professional metadata editor that can read and write standard ID3 and broadcast WAV (BWF) metadata fields, including Artist, Album, Genre, and UCS information, directly into the file, making changes permanent and portable.
4. Is Curlo available for Windows or as a plugin for my DAW? No, Curlo is built exclusively as a native macOS application and is not available for Windows. It is a standalone asset manager, not a DAW plugin, but integrates via drag-and-drop and the local API for seamless workflow bridging.
5. How does Curlo's "Similar Audio Search" work technically? It uses a local AI model to convert the selected audio into a mathematical vector (an embedding) that represents its sonic characteristics. It then compares this vector to pre-computed vectors for all other indexed sounds in your library, ranking them by cosine similarity to find the closest matches.