Answer
What happens if the AI gets something wrong?
It is designed to be wrong safely. Every output has a confidence level; below the threshold the case goes to a person instead of being sent. Anything with money or legal weight is suggest-only, so a human approves before it leaves. Every action is logged and reversible, and corrections become training examples.
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Three layers that catch errors
The first is the confidence threshold: uncertain output never goes out on its own. The second is validation against your systems, so an invoice total that does not match the order is stopped regardless of how confident the model was. The third is the human approval step for anything irreversible.
Compare it to the right baseline
The question is not whether the AI is perfect, it is whether it is better than the current process on a Friday afternoon. A tired colleague handling the fortieth email of the day also makes mistakes, and those mistakes are not logged, not measured and not corrected systematically.
What we do promise is measurement: the error rate is visible on a weekly report, so you can see whether it is falling and where the remaining errors cluster.
Who is responsible
Legally, you are, the same as when a colleague makes an error. That is exactly why the design keeps a person in the loop for anything with consequences, and why the automation records what it did and why, so responsibility can be traced rather than argued about.
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Can it invent a price or a policy?
Customer-facing answers are grounded in your documents and validated against your price list. If the figure is not there, the assistant says it will check rather than guessing.
How quickly can we turn it off?
Immediately, per process, from one switch. The work then falls back to the manual route it came from, with the queue intact.
Do errors get fixed or do they repeat?
Each correction is stored as an example for the same case type, so repeat errors are the ones we specifically review in the weekly check.
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