The operating system for agent-run companies
Let any company hand real work to AI agents, and always know what they did.
Agents fail quietly. A run can finish without an error and still send the wrong thing, and a monthly bill hides which agent spent what. So we build for the moment someone asks what the agent did: the answer should be a link, not a meeting. Where an action matters, a person should decide. And trust should be earned the way it is with anyone new at work: run by run, with the record to show for it.
What we do
Deploy, supervise and improve the agents that work for you.
AgentOS is where companies deploy, supervise and improve the AI agents that do work for them. Every run is on the record, anything sensitive waits for a person's approval, alerts catch failures and silence, and built-in intelligence agents audit the fleet. Agents you already run elsewhere join the same record through our SDKs, the HTTP API or OpenTelemetry, and the whole workspace can be driven from code through the control plane and MCP.
What we believe
Four things we build around.
A person decides where it matters.
Any tool can be gated. The run pauses, the action waits in the approvals inbox exactly as it will be sent, and nothing happens until someone approves or rejects it.
Every run is on the record.
Each tool call, model reply, token count, cost and approval decision is kept, in order. The interesting failures do not throw errors, so you need the steps, not just the output.
Start small, earn trust week by week.
Give an agent one job with a clear owner. Test it before it goes live, with write actions stubbed out, then review its runs every week and widen its scope as it proves itself.
We run on it ourselves.
Our support inbox, outreach, onboarding and social posts run on AgentOS, in our own workspace. What we learn there, including what goes wrong, we write up on the blog.
Proof, not promises
We run AgentOS on AgentOS.
In the 30 days before we wrote it up, about two dozen of our agents did real work in our own workspace: answering support email, finding and writing to prospects, welcoming new signups, drafting and publishing our social posts, and turning product feedback into GitHub issues.
Support2 agents
Email Triage, Support Reply
Sensitive or ambiguous threads are left as drafts for a person
Outreach4 agents
Prospect Finder, Outbound Outreach, Outreach Reply Classifier, Lead Reply Agent
Every first outreach email waits for approval
Onboarding2 agents
New Signup Monitor, Welcome & Onboarding
Every email is built from one fixed template
Social3 agents
Social Content, Daily LinkedIn Post, Daily X Post
Every scheduled post waits for approval
Product2 agents
Linear Feedback Reader, GitHub Issue Creator
Issues are filed for the team to triage, not acted on
Who we are
A small team building AgentOS.
We are a small team, and we use what we build every day. If you want to talk about a workflow, a pilot or the product itself, write to us. We read every message ourselves.
Get in touchHand an agent its first job.
Start with one job that already has a clear owner, gate the part that leaves the building, and watch the first supervised run.