AI errors: how we detect and handle them
“An AI that gets things wrong can cost me dearly. How am I protected?”
The observation
An AI generates the plausible, not the true. It can invent a legal reference, a figure, a name — with perfect confidence. This is what's called a hallucination, and it's the most concrete risk of any AI project. The problem isn't that it happens: it's that it happens without anyone seeing it.
How we handle this topic
Answers grounded in your sources
Our agents answer from your documents and your data, not from "general knowledge". When the information isn't in the source, the agent says so instead of making it up.
Human validation on sensitive decisions
On anything binding (a transfer, a legal document, a customer decision), a human validates. The agent prepares; it doesn't sign.
Drift detection in production
Orbit monitors agents in operation: off-topic answers, forbidden calls, behaviors that deviate. Drift is spotted before it reaches a client.
Full traceability
Every answer is logged with its source. If in doubt, we trace back to what the agent read in order to answer.
What it changes for you
- You know what has been verified, and what hasn't
- No critical decision is made by the machine alone
- If there's an error, you can trace it back to its cause
The limit, stated plainly: No setup brings risk to zero. A reliable AI isn't an AI without errors: it's an AI whose errors are detected, isolated and traceable. That's what we instrument — not a guarantee of infallibility.
Is your situation specific?
This topic is handled case by case. The assessment frames it around your numbers, not in the abstract.