Your reputation lives in models you don't control.

Language models produce text that sounds plausible, and plausible is not the same as true. We have seen invented founding dates, court proceedings that never happened, wrong specifications and outdated prices, delivered with a confidence the customer has no reason to question. Nobody writes a rebuttal to a machine.

The work runs on four layers. Continuous auditing of the outputs for factual errors and negative framing. Correction of hallucinations by verifying the claim, updating the source and documenting feedback to the platform. Protection against synthetic media, with content marking and takedown protocols. And crisis protocols prepared in advance with levels of escalation, so nobody has to invent a response during the incident.

The process during an incident is always the same: document, verify against reliable sources, correct your own sources, align the profiles and measure again. The price is 1000 euro to build it and 200 euro a month for the monitoring. Prevention does more work here than reaction, because consistent facts across public sources reduce the risk of recurring hallucinations.

Take on protection once your name means something. The more often the systems mention you, the more often they will get something wrong about you, and the error travels with the same confidence as the truth. In regulated work, in prices, in deadlines and in anything a customer can check and feel misled by, the cost of one error is not reputational but direct.

The right moment is before the incident rather than during it. A crisis protocol written in advance costs a few hours. The same protocol invented on the fly costs a week, and it is usually written by someone who is in no state at that moment to write it well.