When old missteps still answer for the company you are now.
How AI describes your company once the incident is fixed.
Your company made a mistake in public, fixed it and moved on. AI assistants have not moved on with you.
What goes wrong
An outage, a data incident, a recall or a public backlash draws far more coverage than the fix that follows. Models read that coverage first and keep returning to it. Ask about your security today and you may get a breach from three years ago, described as if it were current, with no mention of the remediation and post-mortem you published. Sometimes the incident is blended with another company’s. A procurement team reading that answer takes the old story as the present one.
What a good account looks like
- The incident is described with its date, in the past tense, as something that happened.
- What you changed afterward is stated next to it and traced to your published remediation.
- Questions about how the company operates today are answered from current material.
How we work on it
We read the questions where the old incident surfaces, including ones that never mention it, such as whether your service is reliable or how you compare with a competitor. Each finding separates what happened, what was fixed and what is current, and shows which source the model used for each. We then propose the wording and pages that state the fix in plain terms, for your team or agency to publish, with the incident still stated as it happened.
Illustrative situation. A payments startup had a two-day outage in its first year and published a full post-mortem. Answers to “Is it reliable for payroll?” still lead with the outage and never mention the redundancy added since.
Start with a free consultation
We agree the scope, depth and outcome you want, and show you a sample of our work on your own website.
Request a free consultation