Nobody was watching the agents.
The industry spent three years making agents more capable and almost none of it on knowing what they are doing while they work. AI Agent Sync was built because the person responsible for the result is the one person who cannot see it happening.
Why we built it
An agent runs for an hour and hands back a result. What you never see is the hour: the loop it got stuck in, the claim it asserted without checking, the point it wandered off the task it was given, or the moment its context filled up and it carried on from memory without knowing what it had lost.
You find out when the work comes back wrong. With a swarm it is worse, because the other agents have already built on it. In April 2026 an agent hit a credential error, searched the codebase, found an over-permissioned token and deleted a production storage volume — taking the backups with it, because they were on the same volume. Nine seconds. The founder found out over the weekend.
Watching is not enough
Logs and traces tell you afterwards. By then the task is finished and the damage is done. Something has to judge the work while it is happening.
The model cannot police itself
An agent asked to check its own work will pass it. Every judgment here is plain code running outside the model, where nothing said in a prompt can widen it.
Evidence has to survive the agent
A record the agent can quietly edit proves nothing. The guard fingerprints its own code, so an unapproved change to it is reported rather than absorbed.
The layer nobody built
Agent platforms are getting rapidly better at reasoning, orchestration, memory and tool use. None of that is what we do, and we are not trying to replace any of it. We looked at what the large platforms actually ship for oversight, and three things were missing from all of them.
| Layer | What is being built | What still is not |
|---|---|---|
| Agent platforms | Reasoning, orchestration, identity, memory, tool use, per-agent tracing | Nothing correlates a fault across several agents working the same task |
| Observability tools | Traces, evaluations, dashboards, cost and latency | They report after the run. None of them stop an agent mid-task |
| AI Agent Sync | Judges every agent while it works, correlates faults across them, stops the one going wrong, and keeps a record it cannot edit | — |
What it actually does
Sees
Reads every agent transcript on the machine — the terminal agents and the chat windows — including the reasoning, not only what the agent says out loud.
Judges
Loops, stalls, prompt injection, claims made without checking, drift from the task it was given, and the moment context is lost and the agent starts working from memory.
Tells you
A panel in the corner of whatever you are working in, quoting the exact sentence it is objecting to, so you can judge it yourself rather than take its word.
Stops it
At the agent’s next tool call, whether the agent cooperates or not. One agent, or the whole fleet.
Puts it back
Every file is copied before an agent writes to it, so whatever an agent changed on its way wrong can be put back.
Proves it
A hash-chained record of what was found, what was stopped and what was released — kept on your machine, where nobody else can revise it.
Where it runs
On your machine. Agent transcripts, findings, policies and audit records never leave it, because there is nowhere for them to go — the product has no server to send them to. The only thing that touches our infrastructure is Stripe billing, which knows your subscription is active and nothing else.
Three rules we refuse to compromise
The agent cannot change its own objective.
The agent cannot expand its own permissions.
The agent cannot certify its own success.