Sentiment correction: fixing what AI systems say about your business.
AI-generated descriptions are not always accurate. Outdated information, amalgamated descriptions, or inaccurate characterisations can persist in AI responses. Sentiment correction identifies these inaccuracies and takes the technical actions most likely to correct them. VERIS is an AI search infrastructure specialist for independent service businesses.
The audit confirms whether Layer 1 infrastructure is in place.
What AI says about your business may not be what you would say.
AI systems generate business descriptions by synthesising information from multiple sources: training data, live web searches, and structured data. The synthesis is not always accurate. A hotel that discontinued a specific amenity may still be described as offering it. A restaurant that changed its cuisine style may still be described as serving the old menu.
Beyond outdated information, AI characterisations can be subtly inaccurate in tone or framing - describing a luxury boutique hotel as budget-friendly or a fine dining restaurant as casual. These characterisations affect which customers choose the business.
Sentiment correction is the technical response to these inaccuracies. It identifies the source data driving the inaccuracy and corrects it at the source: updating llms.txt, correcting schema, updating directory listings, or flagging incorrect external citations.
Inaccuracy identification and systematic correction at source.
Target queries run monthly. AI-generated descriptions captured and reviewed for outdated information, incorrect characterisations, or missing details.
For each inaccuracy, identify where AI is getting the wrong data from: directory listings, outdated reviews, llms.txt, or schema.
Update llms.txt and llms-full.txt, correct schema, update directory listings, and flag incorrect external citations.
Re-query monthly to confirm inaccuracies are replaced. Progress is tracked across recurring crawl and answer-refresh cycles rather than a fixed guaranteed timeline.
All inaccuracies, sources, corrections made, and propagation timelines documented in the monthly report.
What this service does not include.
- Review management or response to customer reviews
- Defamation or false information legal actions
- Removal of accurate negative press coverage
- Social media reputation management
- Crisis communications
- Guaranteed removal of any specific AI-generated description
Common questions about sentiment correction.
No. AI systems cannot be directly instructed to change outputs. What can be changed is the source data those AI systems read - schema, llms.txt, directory listings, and external citations. Corrections are then tracked over monthly checks as those systems recrawl and refresh their answers.
External editorial content cannot be edited by VERIS. If the inaccuracy is in a news article, VERIS flags it and advises the client to reach out to the publication. If it is in a review, VERIS recommends responding with accurate information.
No. Reputation management focuses on review volumes and public perception. Sentiment correction focuses specifically on the accuracy of AI-generated descriptions, which are influenced by structured data and citation sources.
Find out what AI systems currently say about your business.
The free audit includes an automated baseline AI description check across major AI search surfaces.