An AI workforce accumulates something precious: everything it has learned about your business, your preferences, your history together. The uncomfortable question is what happens to all of that on a very bad day. This employee exists for that day. It snapshots your workforce's state on a steady rhythm - the briefs, the records, the accumulated learning - verifies the snapshots actually restore, and when something breaks, brings the workforce back to where it was. A bad day costs hours of history, never the asset.
The state your workforce accumulates gets captured on a steady schedule without anyone remembering to do it. Protection that depends on discipline is not protection.
A backup nobody has restored is a hope. Snapshots get verified restorable on a standing rhythm, so recovery day runs a practiced play instead of a prayer.
When something breaks, the workforce comes back to its recent state: the knowledge, the history, the configurations. The rebuild-from-scratch scenario leaves the table.
When did the last snapshot run, what does it cover, when was restore last verified: answered continuously in your channel, not discovered during the incident.
Your private channel opens the minute you hire. No call, no kickoff meeting, no software to install.
It maps what your workforce has accumulated and what losing each piece would cost - the map that decides what gets protected how often.
Snapshot rhythms, retention, and verification cadence get proposed per asset class. You approve once; the policy runs itself.
Snapshots run on schedule, restore drills verify them, and the status stays visible: covered, current, verified.
Something breaks, the practiced restore runs, and the workforce is back with its memory intact. The disaster genre becomes an operations footnote.
Like every Tenfold employee, this one runs one opinionated method: a backup exists only once a restore of it has succeeded, coverage follows the cost of loss, and status is reported continuously - discovering your backup posture during an incident is the failure. When the field moves, the method moves, and you do nothing to get the update. Here is the whole method.
It snapshots and restores through grants you make once, in your portal's Access tab. Restores that touch live state wait for your explicit approval, credentials never appear in chat, and you can revoke access yourself at any time.
The state your workforce accumulates: the Company Brief, the working records, the learned preferences and history that make your employees yours. The onboarding map names it all, and you approve the coverage.
Because restores get rehearsed: on a standing rhythm it verifies snapshots restore cleanly and reports the result. Verified is the only status it ever calls a backup.
No - any restore touching live state waits for your explicit approval. Snapshots run ambient; recovery is always a decision.
Hours to the most recent snapshot, on a rehearsed path. The exact rhythm - and therefore the maximum history at risk - is the policy you approve.
Reliability lowers the odds; it never zeroes them. The workforce's accumulated learning is an asset that appreciates - this role is the insurance that lets you build on it without a flinch.
An AI employee that watches every employee in your AI workforce and alerts on silent failure - the workforce management layer that keeps automated work trustworthy.
An AI employee that reads across every department each morning and hands you one digest: the consolidated waiting-on-you queue, per-department notes, and the cross-signals.
An AI employee that reads your inbound messages and routes each one to the right employee or human - so a growing workforce has a front door instead of a pile.
An AI employee that processes incoming bills, categorizes them, flags what looks off, and queues everything for your approval - so paying bills takes minutes, not an afternoon.
Requesting this role moves it up the roster - requests set the order roles open for hire, and you will hear the moment it opens.
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