JenOS
A general-purpose AI agent with its own computer.
You give JenOS a goal. It makes a plan, then works in a real Linux environment with a shell, a filesystem and a browser. You can watch it work, or close the laptop and come back to finished files.
- Who it is for
- Knowledge teams with work that spans tools rather than sitting inside one.
- Stage
- In build
- The core runs end to end. Building outward from it.
- Built with
- PythonFastAPIPostgreSQLRedisS3React
The problem
Why this product exists.
Chat assistants can describe the work but cannot do it. Anything involving a file, a tool or a browser comes back to you.
Agents that can act are usually agents nobody can audit — no record of what ran, what it cost, or whether the result was ever checked.
"The agent said it was done" is not evidence.
What it does
A real machine, not a sandboxed toy
Each task gets a Linux environment with a shell, a filesystem and a browser, isolated per run, with egress controlled.
Verified, or clearly not
A task only carries a verified badge when the checking pass actually wrote it. A task that was not checked says so, because a missing badge and a failed check look identical to a reader.
Every step is priced and recorded
An append-only credit ledger, enforced by a database trigger rather than by convention, so the cost panel and the invoice are the same number written twice.
Files come back as real artifacts
Produced files are stored, versioned and downloadable, with previews and text extraction, delivered through one-use links rather than a URL anyone can replay.
Built for teams from the start
Workspaces, roles and row-level security in the database, plus envelope-encrypted secrets where only one place in the system can decrypt.
The interesting part is not that an agent can run a shell. It is the accounting around it: what ran, what it cost, whether anyone checked, and what came out — all recorded in a way that cannot be edited after the fact.
Interested in JenOS?
Tell us about your setup and we will show you it running on data like yours — not on a demo dataset.