Position
Artist-first AI
ANYANO exists because we think the interesting question is not how quickly a machine can produce a song, but whether a machine can be genuinely useful to someone who already makes music.
Principles
Four commitments
- 01
AI should extend artistic identity, not erase it
A tool that pulls every user toward the same competent average is not helping artists; it is diluting them. Training on an artist's own material is the most direct way we know to point the technology the other way.
- 02
Artists should control the material used for personalization
You choose what goes into a dataset, you confirm your rights before a run, and you can delete material and Sounds. Personalization without that control is just data collection with better marketing.
- 03
Personal creative models should stay under artist control
A Sound is scoped to the account that trained it. It is not published, not browsable, and not used to train models for other customers.
- 04
AI should offer possibilities, not decisions
Generation produces candidates. Which candidate becomes music is an editorial act, and the product is designed so that act stays with you — that is what Directions are.
Consequences
What this rules out
Building this way closes doors deliberately. We are not building "make a song like [famous artist]", voice cloning of people who did not consent, or a public catalogue of other artists' Sounds to browse. Those features would be commercially tempting and would contradict the premise.
It also means we cannot promise the thing generic generators promise most loudly: a finished song from one sentence, with no material of your own. ANYANO needs you to bring music. That is the trade.
Standards
On honesty in AI music marketing
The AI music category has a credibility problem, and a lot of it is self-inflicted: invented statistics, testimonials from artists who do not exist, absolute privacy claims that no architecture supports, and progress bars that mean nothing. We would rather be specific and less impressive.
So: we describe what is implemented, we name where third-party processing is involved, we do not publish research we did not conduct or case studies from artists who have not used the product, and we do not display fake precision about jobs the backend cannot measure. When we get something wrong, the fix is to change the claim.
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What we think the technology is for
The most valuable moment in making music is also the cheapest: the sketch, before anything is committed. That is where having twenty plausible options costs you nothing and having none costs you weeks. A model trained on your own catalog is unusually good at that moment, because its suggestions already sound like they could be yours.
Everything after the sketch — performance, arrangement, mixing, taste, meaning — is still yours to do. We are not trying to automate it, and we do not think artists want that.
Related
Keep reading
The artist is the source. ANYANO is the instrument.
Train a Sound on your own music and keep the decisions.