Home Artificial IntelligenceArca Is Now Open to All, Paying People for the AI Sessions Already on Their Computers

Arca Is Now Open to All, Paying People for the AI Sessions Already on Their Computers

by Joseph Wilson
3 minutes read
Arca Is Now Open to All, Paying People for the AI Sessions Already on Their Computers

The desktop app from the team behind Brevis has dropped its invite requirement and is available to anyone on Mac and Windows.

HONG KONG: Arca, the desktop app from the team behind Brevis that pays people for the AI sessions they’d otherwise throw away, is now open to the public. Since November 11, anyone can sign up with an email address or a Google account, with no invite and no waitlist. The app finds the session history that AI tools already keep on a user’s computer, lets the user choose which sessions to submit, strips sensitive details on the device before anything is uploaded, and pays for the sessions that are approved.

A growing share of knowledge work now happens inside AI tools. A person steers a model through a task, corrects it, discards what fails and keeps what holds up. Each session leaves a detailed record of that work: the back-and-forth, the dead ends and the fix that finally worked. Those records pile up by the thousands on people’s computers, and once the window is closed they are worth nothing to the person who did the work. Arca puts a value on them.

From session to payout

Arca works with tools people already use, including Claude Code, Codex, Cursor and Claude Desktop. Once the app is installed, it shows the sessions it has found on the machine, including past ones. The user picks a session to upload, Arca anonymises it on the computer before it leaves, and a quote range comes back. From there the user either confirms, which sends the session for review, or withdraws, in which case the upload is deleted. Approved sessions are paid weekly.

Arca reads only the sessions that are already on the user’s computer, and it lists everything it finds. Nothing uploads in the background, and nothing leaves the device until the user picks a session and confirms. Before a session is uploaded, Arca strips names, file paths, account details and keys, and further anonymising runs on Arca’s side.

“Every AI session is a record of real thinking and real work, and until now the person who did that work got nothing for it,” said Michael, co-founder and CEO of Brevis. “Arca lets people see what their sessions are worth and decide for themselves what to share. We opened it in small batches first to get the experience right. Today it’s open to everyone.”

Any field, not just code

Arca is for anyone doing real work with AI, whether that is code, contract reviews, research or long working conversations. Sessions with Claude Opus and Fable, and with the latest GPT models in Codex, qualify today, with more to come. Very short sessions don’t qualify, and every submission is reviewed before it pays. Connecting GitHub is optional: it strengthens a user’s profile, which can raise the value of their sessions.

Arca carries the principle behind Brevis’s verifiable computing work into a new domain: things you can verify are worth more than things you have to trust.

Availability

Arca first opened on October 13 as invite-only early access, admitting users in small batches. The invite requirement ended on November 11. Arca is free to use and available now for Mac and Windows at arca.market.

The Arca Launch Challenge runs through November 30 and adds $10,000 in prizes on top of regular payouts for approved sessions.

About Arca

Arca pays people for the AI sessions they’d otherwise throw away. The desktop app finds the sessions people’s AI tools already keep, lets them choose what to share, anonymises sessions on the device before upload, and pays for approved sessions. Arca is built by the team behind Brevis. Learn more at arca.market.

About Brevis

Brevis builds verifiable computing infrastructure. Its zero-knowledge proving technology, including the open-source Pico zkVM, lets applications prove the results of complex computations. Learn more at brevis.network.

Media Contact

Nicolas Tang

nicolas@brevis.network

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