Train one AI employee to handle email — with evidence before trust.
Brief it in Chat, forward one real email, inspect the held reply and evidence, correct the same employee, and use the proof to decide one Action's trust setting. Current safety floors can still hold work.
“Hi — can you tell me if you can fit a same-day repair in this week? It’s fairly urgent.”
“Thanks for reaching out — yes, we have same-day slots this week. What’s the best number to confirm a time?”
From one forwarded email to a better-trained employee.
The email job is one concrete door into Vavio’s wider platform: brief, connect, inspect, correct, and decide what to trust next.
1. Brief one employee in Chat
Tell the same AI employee which email matters, what a safe reply sounds like, and what should always be held for you.
2. Forward the work it needs
Start with email forwarded to its Vavio address. The employee reads that source, classifies urgency and type, and applies the rules you taught it.
3. Review held work and evidence
It prepares the exact recipient, subject, and reply, then shows what it checked and why it held the draft. Nothing was sent.
4. Correct the same employee
Correct the judgment or tone in Chat. The correction becomes visible Training — a rule or preference you can edit or remove — and the next similar job shows whether it stuck.
5. Decide trust from evidence
Use the run evidence to choose that Action's trust setting. Current safety floors can still hold work for approval.
Production test · company-owned account
What Vavio has actually proved with Gmail.
This is product evidence, not a testimonial or a claim about a customer’s inbox.
Two consecutive approval-gated cycles
On Vavio's company-owned, already-connected production Gmail account, two consecutive marked cycles read real mail, wrote a draft that Vavio verified at Gmail, held the reply, and delivered it only after explicit owner approval.
What those cycles do not prove
That is Vavio's product test, not a customer result. A stranger connecting their own Gmail through Vavio's branded consent still awaits Google's restricted-scope verification; it does not guarantee a recurring inbox result for a new owner, and unattended sending remains unproved.
Trust grows from evidence, not a promise of autopilot.
Vavio shows the work, the reason, the cost, and the correction. That proof informs the Action setting; it does not erase current safety floors.
One calm Review queue
Held work waits in Review with the exact action visible, so the exception is clear without turning every run into noise.
Evidence, not a status label
Inspect what the employee checked, why it acted or held, what changed, and what the run cost.
Corrections become visible Training
When the judgment is wrong, correct it in plain language, inspect the rule or preference saved in Instructions, and edit or remove it.
The proof boundary stays visible
Start self-serve with forwarded email. The company-owned Gmail proof below does not turn a new owner's connection, recurring inbox result, or unattended sending into a promise.
Keep related work on the same employee when it shares context, channels, data, approval rules, or intent. Create another employee only when the job boundary is genuinely different.
Train one employee for the email job.
Start free, brief the job in plain language, and keep shaping the same employee through visible Training and evidence from its runs.
Free trial. The self-serve example ends in held work; the production Gmail proof used explicit owner approval and does not establish unattended sending.