"Audit trail" is a phrase from accounting and compliance: a log an auditor can follow. Most AI tools that promise one give you a stream of events a developer could follow and an owner never will. If an agent is going to act in your inbox and your calendar, the record of what it did should read like a receipt: one page per run, in plain words, that answers the question you will actually ask, which is "why did that happen?"
This is what Tensor Autonomous records about every run, why each line is there, and what it lets you do afterwards.
What a receipt holds
Every time a responsibility runs, Tensor keeps:
- What was asked. The request that started it: the tenant's email, the showing request, "follow up on my open quotes today."
- What it read. The records it looked at to do the job: the listing facts, the requested day on the calendar, the quotes sheet. Not a copy of your mailbox; the things this run used.
- What it proposed. The exact change it put in front of you: the event with its time, the row with every cell, the reply with its text.
- Who approved it, and when. Your click, with the time, or the limit it ran under if you had set one.
- What it wrote. The event, the row, the draft, as written.
- The read-back. After writing, Tensor reads the record back from where it was written and compares it with what it sent. The receipt shows the fields that matched, and says so if one did not.
That last line is the one most audit trails lack and the one that makes the rest trustworthy. "I wrote it" is a claim; "I wrote it, read it back, and it matches" is a check.
Why plain words
An owner reading a receipt on Friday should not need to know what an API call is. So the receipt names the calendar or sheet it wrote to, not an endpoint, and says who approved it and when, not a user ID. When a tenant asks why they were told Thursday at 2, you open the run and the answer is on one screen.
What the receipt lets you do
- Answer questions. Why this reply, why this time, who said yes.
- Undo. Next to each write in a responsibility's work, Undo removes what Tensor created (an event, added rows, a draft); you read exactly what will be removed and confirm, and if it has since been changed, Tensor leaves it alone.
- Roll back. Each responsibility's guide is versioned; if a change to how it works made things worse, go back to the version that worked.
- Pause and read. A responsibility can be paused while you read its recent receipts, then resumed.
The honest limit: an email that has been sent cannot be unsent. Tensor's starters leave drafts for you to send for exactly that reason; every send waits for your OK; limits can't cover sending.
What a thin audit trail looks like
- It logs that the agent ran, not what it changed.
- It logs the output but not the input, so you cannot tell whether the agent read the right record.
- It logs an action but not an approval, so you cannot tell who said yes.
- It logs the write but never reads it back, so you cannot tell whether it landed.
If a vendor's trail has any of these gaps, you will find out the day something goes wrong, which is the day you needed it.
The receipt in the live demo
The live demo is a real run on sample data, and it ends with the receipt: the task, your words, the result, and the row or event as read back from Google. It is the same receipt a customer sees for their own runs.
Where to start
- Try it live: approve one change and read its receipt.
- Security: what is kept, what is not, and how access is removed.
- Product. Plans from $149 a month.
Related reading
- Automated approval: what should run by itself, and what should wait for you
- AI agent governance for a small business
- Approval workflow software, or an agent that asks first?
See it in a demo
The run, the approval, the write, the read-back: one receipt.