Enables AI models to analyze audio files through numerical fingerprints, pitch tracking, and visual spectrograms without requiring direct audio playback. It provides tools for comparing audio iterations and detecting patterns using token-efficient analysis operations.
Enables AI agents to analyze audio files, extracting tempo, key, beat drops, volume surges, high tones, loudness, brightness, and structure, and returning structured JSON and visualizations.
Enables AI agents to analyze local or URL-hosted audio files with TrackTag, returning professional music metadata such as BPM, key, genres, moods, and 35+ fields. Runs locally on your machine, using your TrackTag API key and credit balance for analyses.
Enables audio file analysis using Google's Gemini multimodal models with support for additional context and system instructions to guide the model's behavior.
Enables AI assistants to transcribe audio and video from URLs or local files with high accuracy, speaker diarization, 119 languages, and word-level timestamps, while also supporting transcription management and caption export in SRT, WebVTT, or plain text.
