Pianolyze vs Taste Lab: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Pianolyze and Taste Lab — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
P
Pianolyze
Pianolyze
In-browser, on-device piano transcription: drag & drop audio to get a piano-roll view and slowed playback with no uploads.
Key features
- On-Device Transcription: Runs the transcription model fully in the browser so audio is processed locally, minimizing latency and ensuring recordings are not uploaded to remote servers.
- Drag-and-Drop Audio Input: Accepts common file formats (MP3, WAV, FLAC, M4A) via simple drag-and-drop to quickly start analysis without complex imports.
- Piano-Roll Visualization: Generates an interactive piano-roll view of detected notes, showing pitch and timing to help users inspect performance details visually.
- Variable Playback Speed: Allows slowing down audio playback to inspect fast passages or subtle timing details while keeping the visual transcription synchronized.
- Local Privacy by Design: Architecture avoids cloud uploads, making the tool suitable for users concerned about confidentiality of recordings and intellectual property.
- Immediate, Low-Latency Analysis: Browser execution provides near-instant transcription and visualization for rapid iteration during practice or review.
- On-device piano transcription performed in the browser (no uploads to a server)
- Drag-and-drop support for MP3, WAV, FLAC, M4A audio files
- Piano-roll visual representation of detected notes
- Playback controls including slow-down for practice and analysis
- Local processing to preserve user privacy and eliminate file transfers
Best for
- Practice Analysis: Students and teachers can upload practice recordings to inspect missed notes, timing, and articulation using the piano-roll and slowed playback.
- Performance Review: Pianists can quickly analyze live or recorded performances for phrasing and timing issues without sending files to third-party servers.
- Music Transcription Prep: Musicians can extract note-level information from recordings as a starting point for creating scores or MIDI arrangements.
- Rehearsal Feedback: Teachers can generate visual feedback for pupils showing where notes deviate from intended pitches or rhythms during lessons.
- Research & Analysis: Music researchers can use on-device transcriptions to study performance characteristics across takes while preserving data privacy.
- Musicians transcribing piano recordings into a piano-roll for practice and analysis
- Students slowing down passages to learn difficult sections
- Composers extracting note information from recorded takes
- Music teachers demonstrating performance details visually without uploading student recordings
- Quick on-device analysis of piano audio where privacy is required
Taste Lab
Sen Lin
Taste Lab is a Claude Code skill that turns any URL into a complete design context: design tokens plus the reasoning and trade-offs behind every choice.
Key features
- Design Map Extraction: Captures every color, font weight, spacing value, radius, and shadow with exact px/hex/ratio citations across 20 measurement categories.
- Taste DNA Inference: Derives four design principles, each with a Trigger, Decision, Reason, Evidence, and Trade-off explaining why each choice was made.
- Four-Agent Pipeline: Runs Extract, Detect Patterns, Infer Taste, and Observer stages, each reading the page through a sharper lens.
- Anti-Slop Quality Gate: A final critic stage runs anti-slop checks and validates JSON before writing output.
- Dual File Output: Writes a {domain}.md and {domain}.json that any AI agent can build from.
Best for
- Cloning Design Systems: Give an AI agent a complete, reasoned design context to rebuild a site's look and feel.
- Design Reviews: Understand the deliberate trade-offs behind a website's visual decisions.
- Agent-Assisted Frontend Work: Feed structured taste files into coding agents so they make the right call on unseen pages.