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Audio & Music/Composition & MIDI

Spark Chords

AI chord trigger from text input

Visit mozaic.io

External link. Not endorsed — curated for usefulness.

What is Spark Chords?

Spark Chords is an AI-powered chord generation tool made by Mozaic that converts text descriptions into playable musical chord progressions. Users input text prompts describing a mood, style, or harmonic concept, and the system generates matching chord sequences that can be triggered and played back in real time or exported for use in DAWs and music production software.

The tool targets musicians, producers, and composers seeking rapid harmonic inspiration or who lack formal music theory training. Rather than manually selecting chords or searching chord charts, users describe what they want in natural language—such as "melancholic minor progression with jazz extensions" or "uplifting major chords for a pop hook"—and Spark Chords generates options instantaneously. The generated chords display as both standard notation and interactive keyboard visualizations, allowing immediate audition and iteration. The interface supports MIDI export, making it compatible with major DAWs including Logic Pro, Ableton Live, FL Studio, and Cubase. Spark Chords integrates with the broader Mozaic ecosystem, which focuses on AI-assisted music creation tools.

Pricing operates on a subscription model with tiered access; specific cost varies by plan tier and usage limits. The freemium structure allows limited daily generations for new users, with paid tiers unlocking higher generation counts and advanced features like batch chord creation and premium sound banks.

The workflow appeals particularly to producers working against deadline pressure, non-traditional musicians building harmonic literacy, and anyone exploring chord palettes outside their native genre. Competitors in this space include Hookpad (which combines AI suggestions with music theory education), Amper Music (broader AI composition), and Chordify (which extracts chords from existing songs). Spark Chords distinguishes itself through text-to-chord directness and minimal interface friction between description and play