How do you triage the moderation queue against your policy?
A moderation triage AI Employee that reads each item as it lands in the queue, checks it against your policy, and routes it to the right reviewer with a recommendation and the rule it cites. It recommends and routes; a human actions every call.
×
The moderation queue fills faster than a team can read it, and every item needs the same first pass: read it, hold it against the policy, decide which rule it touches, and route it to whoever should make the call. Most items are clear cut in both directions, obviously fine or obviously not, but they still sit in the same undifferentiated pile as the genuinely hard ones, and a reviewer has to open each to find out which is which. So the queue backs up, the borderline items that most need a careful human read get the same rushed glance as the easy ones, and the policy gets applied unevenly depending on who's clearing the backlog that day. The bottleneck isn't the judgment. It's that a person has to do the whole read and sort before the judgment can even start.
As each item lands in the queue, the moderation triage AI Employee reads it, checks it against your policy read only, and routes it to the right reviewer with a recommendation and the specific rule it cites. It recommends and routes so the reviewer opens a presorted queue with the reasoning attached, but a human actions every call. It never removes, approves, or bans on its own.
See exactly how the work gets done.
Fires as items land
Each new item in the queue triggers a run, so it arrives at a reviewer already checked and routed, not sitting in an undifferentiated backlog.
Carries your policy
Your moderation policy, what each rule covers and where the lines sit, travels with it as skills and memory, updated as the policy changes, so every item is measured against the same standard.
Reads the content read only
It reads each queued item from the content store read only to check it against policy. Credentials stay in memory, never written to disk, never exposed to the model.
Routes with a recommendation
It routes each item to the right reviewer and attaches a recommendation with the exact rule it cites, so the reviewer sees the reasoning, not just a verdict.
A human actions every call
It never removes, approves, restricts, or bans on its own. Every moderation action is taken by a named person who reviewed the recommendation.
Runs in your environment
Every run is isolated inside your own infrastructure, reaching only the content store and the channel it routes to. Your content never leaves.
Reads content read only
It reads each item to check it against policy. It never edits, hides, or deletes content itself.
Recommend and route only
It never removes, approves, restricts, or bans. Every enforcement action is taken by a named person who actioned it.
Cites the rule, not a verdict
Each recommendation names the specific policy rule it's based on, so the reviewer checks the call against the policy before acting.
You own the policy
The moderation policy the recommendations are measured against is yours, versioned and changed on your terms, not in a vendor dashboard.
The moderation queue that used to hit every reviewer as one undifferentiated pile now arrives presorted, each item routed with a recommendation and the rule behind it. The AI Employee does the reading and sorting; a person makes every call.
As they land
Items checked and routed before a reviewer opens them
Cites the rule
Every recommendation names the policy line it's based on
Recommend and route
The AI Employee sorts; a human actions every call
Our free AI audit shows you where AI fits, what your security risks are, and gets your first AI employee working.
How does YP run operations across your tools from one Slack thread?
Reachable from any Slack thread, it runs cross platform operations (onboarding, reviews, provisioning, billing changes) across the systems you connect, holding irreversible steps for a named human.
×How do you make sure every new vendor is vetted before you pay them?
Validates every new vendor's W9, banking form, and signed contract against one fixed checklist, records the result to your register, and flags anything missing or invalid. It never approves a vendor and never sets up payment.
×How do AI Employees turn every meeting into notes and assigned action items?
Turns each finished call into structured notes and files every action item as a ticket routed to its owner, flagging anything it can't confidently assign for a person.
×