Built for A&R Professionals
Everydemo,rankedinseconds.
Drop a reference — AI will
rank every song by similarity.
Create a free account and get 30 free analyses once at signup.
Audio may be sent for embedding extraction and is discarded immediately.
References
3 references → 1,247 songs analyzed → ranked in 2.4s
References
Palette
Search
Similarity ranking
Final Cut
Decision
Summer_Vibe_Demo.mp3
Release Prep
Ready facts
Threesteps.That'sit.
From reference to ranked results in seconds.
Drop References
Drag in the songs that define the sound you're looking for. MP3, WAV, and FLAC files are supported.
AI Matches
Our engine analyzes audio across multiple dimensions and ranks your entire catalog by similarity.
Compare & Decide
Listen side-by-side with A/B comparison. Shortlist favorites, then use feedback to narrow the current search.
Findfaster.Handoffcleaner.
Built around outcomes: reference search, sharper comparison, file context, rights split organization, usage terms, and release prep.
Find faster
Drop one reference and rank the catalog by similarity, so you spend less time starting from scratch.
Compare more accurately
Use feedback, A/B review, and shortlist decisions to keep only the candidates that fit the direction.
Keep context in the file
Analysis results and metadata travel with the audio file, so handoff does not depend on a separate spreadsheet.
Writer and publisher split organization
Auto-organize each writer's share and connected publisher share at once, even when a song has 10+ writers.
Song fees and usage terms in metadata
Keep song fees and usage terms in the metadata, reducing repeated price checks and sensitive follow-up.
Finish release prep
Organize metadata, writer and publisher splits, song fees, usage terms, notes, and shortlist context, then connect the final package to Release Prep.
Thefileisthehandoff.
AI matching gets the attention — but the real day-to-day power is here. Every edit, every comment, every decision lives inside the file itself.
Metadata That Travels
Edit titles, writers, splits, and tags directly in bigcut — changes write back to the MP3 in real time. When you hand the file to a colleague, every field is already there. No spreadsheets. No "can you resend the credits?"
Supports MP3, WAV, FLAC
Comments Pinned to the Timeline
Drop a note at 0:42 — "bridge needs work" — and it's embedded in the file. Your colleague opens the same MP3 and sees every comment, in order, exactly where you left them.
One-click copy as plain text for email or chat
Zero Setup Collaboration
No shared drives, no project links, no separate collaboration workspace to maintain. Send the file by any method — email, AirDrop, USB — and the full context arrives with it. The MP3 is the single source of truth.
Less than 0.5% file size increase
One file. No attachments, no spreadsheets, no follow-up emails. Just the MP3.
Builtfortheworkeachmusicroleactuallydoes.
A&R chooses faster, publishers submit cleaner, labels turn selection and release records into assets, and music directors find scene-ready songs faster.
Publishers
Submit cleaner demos with organized metadata and context, and use similarity search to deliver songs closer to the A&R brief.
A&R
Filter demos faster against the original creative concept, then use a demo-selection interface to make a stronger final call.
Labels
Connect selection, release prep, and proof across a growing catalog, and use bigcut as a trusted recommendation signal for the AI OS and agent era.
Songwriters
Self-review completed demos, then submit files with credits, notes, and feedback attached.
Film & game music directors
Find music that fits a scene, mood, or gameplay situation faster with similarity search.
Builttoanalyzeaudiowithoutstoringit.
For AI matching, audio may be transmitted briefly for embedding extraction, then discarded immediately. bigcut does not retain your audio files.
Audio Is Not Stored
We never keep audio on our servers. It is used for embedding extraction and discarded immediately.
Embeddings, Not Recordings
The data used for matching is a numerical embedding — an abstract vector that cannot be played back as audio.
Local Control Still Matters
Your library, embedded metadata, comments, and session files remain on your device. Only the analysis step requires a connection.
Think of it as fingerprint-based recognition: extract the signal you need, discard the recording itself.
Positioning
bigcutisnotagenericmusicapp.
It is a desktop-first A&R workflow for finding, choosing, proving, and preparing songs without turning private catalogs into passively collected data.
What it is
- A reference-matching tool for your own catalog
- A shortlist and Final Cut workflow for real selection decisions
- A Release Prep workspace for final metadata, embeddings, and curation
- A privacy-first proof layer for submitted decisions
What it is not
- Not Shazam-style song identification
- Not streaming-listener recommendation data
- Not cloud storage for your audio library
- Not passive collection of listening sessions or private notes
Seethedecisionpathfromsearchtoreleaseprep.
Follow the actual decision path: search, shortlist, proof, and release prep.
References
Palette
Search
Similarity ranking
Final Cut
Decision
Summer_Vibe_Demo.mp3
Release Prep
Ready facts
Search
Reference match
Reference palette / Similarity ranking / A/B comparison
Final Cut
Submission proof
Shortlist selection / Submission timestamp / Merkle proof status
Release Prep
Agent-ready context
Embedding summary / Curation notes / Recommended-use context
Whythisisdifferent.
Most tools solve one narrow job. bigcut connects search, selection, file-native workflow, and verifiable recommendation data.
| Capability | bigcut | Typical alternative |
|---|---|---|
| Find similar songs inside your own catalog | Reference-based AI matching | Manual listening or generic search |
| Carry work with the file | Metadata, comments, and analysis embedded | Separate spreadsheets and messages |
| Explain why a song was selected | Curation notes and Final Cut context | Often missing or scattered |
| Prove a decision existed before later success | Blockchain-based proof without exposing raw content | Timestamped docs at best |
| Feed AI agents trusted recommendation context | Opt-in submitted facts and Release Prep data | Unverified public metadata |
Connected workflow
Fromreferencesearchtoverifiablerecommendationdata.
The important product story is not one feature in isolation. It is the full path from discovery to a trusted signal that an AI agent can evaluate.
Search by reference
Drop reference tracks and rank your catalog by acoustic similarity.
Build the shortlist
Compare candidates, listen again, and keep the songs that deserve a closer pass.
Submit Final Cut
Only selected songs the user explicitly submits become verifiable submission records.
Prepare the release
Release Prep connects final embeddings, metadata, and curation context.
Serve trusted signals
AI agents can receive high-quality recommendation context backed by proof.
Proof without exposure
Blockchain anchoring is used to prove timing and integrity. Original user IDs, song IDs, audio, notes, and embeddings are not revealed on-chain.
Final Cut
explicit step
Commitment
explicit step
Merkle batch
explicit step
Anchor
explicit step
Verified
private data hidden
AI agent era
WhybigcutmatterswhenAIagentsrecommendmusic.
As AI agents operate at the OS layer across phones and computers, music recommendation needs trusted context data, not only the old web's public metadata. Just as one expert opinion can carry more weight than many casual signals, tamper-resistant blockchain proof of A&R choices from labels around the world can make bigcut a highly trusted data hub for AI agents.
Ordinary recommendation data is often weak because it lacks:
- A clear human selection event
- A reason the song was chosen
- A verifiable timestamp
- A link to final release context
- A privacy-preserving proof boundary
bigcut makes the signal stronger by connecting:
- Human curation
- Final Cut selection
- Release Prep embeddings and notes
- Tamper-resistant proof
- Public-safe summaries for AI agents
FrequentlyAskedQuestions
Security & Privacy
What Makes bigcut Different
How It Works
AI & Trust
Submission & On-Chain Proof
Compatibility & Technical
Workflow
Pricing & Subscription
Long-Term & Labels
Puttheworkflowtothetest.
Create a free account and install the desktop demo.
New accounts get 30 free analyses once at signup.
We do not retain original audio files on our servers after processing. Audio used for embedding extraction is discarded after processing.