Reputation repair is the professional process of rebuilding a damaged online presence after a crisis, hostile campaign, or sustained period of negative search visibility. It involves correcting inaccurate information, removing or suppressing damaging content lawfully, publishing authoritative positive content, improving search and AI visibility, and restoring stakeholder trust.
Reputation repair is sequenced, not simultaneous. The first phase is containment — ensuring the acute incident is addressed and no longer generating fresh negative material. The second is correction — removing or deindexing unlawful or defamatory content, correcting inaccuracies at the source, and contextualizing what cannot be removed. The third is reconstruction — publishing and placing authoritative content so that accurate information dominates search and AI results. The fourth is maintenance — monitoring and reinforcing the repaired visibility so the damage does not return.
A central principle of reputation repair is the distinction between what is removable and what is suppressible. Lawful, accurate material cannot be removed and should not be pursued through removal attempts that will fail and amplify. It can, however, be suppressed — out-ranked and out-weighted by authoritative content. Unlawful, defamatory, or policy-violating material can be removed at the source or deindexed, and that is the higher-leverage remedy where it applies. Conflating the two categories is the most common error in repair strategy.
Reputation repair also addresses the AI-summary layer explicitly. A damaged AI summary persists long after the source content is corrected, because it is embedded in training data and cited indexes. Repair that fixes search results but not AI summaries leaves a live reputation problem that resurfaces every time someone asks an AI about the entity.
The timeline for reputation repair is measured in months, not days. Search visibility improvement typically requires 60–90 days for content strategy to begin ranking, with significant improvement for competitive names taking 6–12 months. AI representation changes faster on real-time platforms and slower on training-based models. Honest scoping of this timeline is part of professional repair — promises of overnight results are a red flag.