Run a media OPC,
one person + agents.

A one-person company for audio. Pick a niche — founder interviews, crypto roundups, conference talks. Drop sources in. Agents clean, diarize, transcribe, translate, and re-voice them. Revenue flows to you, to the speaker, to the protocol.

Read the docs

Drop a URL. Get a Chinese episode back.

src ▸
compute:target: 中文 (more soon)
01
fetch source
queued
02
denoise + reconstruct
queued
03
diarize speakers
queued
04
transcribe (EN)
queued
05
translate → 中文
queued
06
voice convert
queued
07
polylingua dub
queued
08
publish to feed
queued

70 / 15 / 15.
In that order.

The publisher running the OPC takes the largest share — they took the risk and made the call. The speaker gets paid every time their voice appears, in any language. The protocol takes the smallest cut to fund the rails.

Revenue / token layer is on the roadmap — design shown here.

70%
Publisher
the operator running the show — picks sources, sets language targets, owns the niche
15%
Speaker
goes to whoever's voice is in the audio, paid out per use, in every language
15%
Protocol
funds the rails — pipeline, storage, the open-source tools

Things people ask before signing up

Do I need to know how to code?

Not for the hosted flow — the admin dashboard runs the pipeline. The tools page is for people who want to fork the stack or embed it in their own product.

What about copyright on source material?

Publish only what you have the right to. Every episode credits the original creator and links back, and the Chinese audio is clearly labelled as an AI-generated dub.

Whose voice is used?

The speaker's own — reconstructed by voice conversion (Plan C) or cloning (Plan B). The output is labelled AI-generated and can be watermarked.

What does it cost?

Mostly compute. Local models (Ollama + MLX + seed-vc on Apple Silicon) run for free on your own machine; hosted APIs are pay-as-you-go.