What you get in a ModelSaid AI Clarity report

A ModelSaid AI Clarity report turns scan evidence into an understandable assessment of where a business appears in AI answers, how it is described, which competitors surface, and what to improve next. The emphasis is clarity: concrete actions plus the reason each action matters, not a score without context. Reporting is included from Monitor upward. Check pricing for current plan terms and use the free visibility scan when you only need a teaser baseline.

The report begins with an answer-first assessment

Decision-makers need the conclusion before the methodology. The report frames the current visibility picture in plain language, then lets reviewers inspect supporting observations. A useful assessment separates presence from quality: being named is different from being recommended, and a recommendation containing a false fact is not a clean win. The report's role is to turn those distinctions into priorities without implying that an API observation exactly reproduces every personalized consumer-app answer.

Visibility evidence has market context

ModelSaid runs questions in the business's scan language and relevant market context. It evaluates major assistants including ChatGPT, Claude, Gemini and Perplexity, with provider coverage designed to remain extensible. Depending on plan, scan scope differs: Monitor uses a standard grounded set, while Agency and Agency Pro use a full question tier and compare searched with knowledge-only answers. That distinction helps explain whether current web retrieval or built-in knowledge is doing the work.

"You were not mentioned" is incomplete unless the business can see what appeared instead. A Clarity report surfaces competitor patterns around relevant questions, helping the team ask why another option was supportable. The explanation may point to clearer decision information, stronger external corroboration, better entity consistency or genuine product fit. It should not encourage copying competitors or manufacturing consensus. The goal is to find a legitimate evidence gap the business can own.

Technical findings connect answers to readiness

AI visibility is not only a content question. Site access, robots policies, structured facts and clear page signals can affect whether current information is retrievable and understandable. The report can organize technical readiness findings alongside answer evidence, while scheduled monitoring continues weekly on Monitor and daily on Agency tiers. Use the schema validator to examine a specific JSON-LD implementation; never add markup for claims that users cannot verify on the page.

• What was observed and which business question it affects.
• Why the issue may matter for discovery, accuracy or customer trust.
• Which owned page, external fact or technical element deserves review.
• What evidence supports the recommendation and what remains uncertain.
• How the team can verify progress in a later comparable scan.

Monitor retains twelve months of trends and schedules monthly visibility rescans, allowing a report to become one chapter in a time series. Alerts flag changes between ordinary review meetings, and two monthly on-demand scans can investigate important events. Agency tiers add portfolio delivery and white-label reports, with the agency's brand on shared links and printable PDFs. White-labeling changes presentation, not the obligation to disclose sound methodology and limitations.

1. Validate each factual premise with the business owner or authoritative source.
2. Rank actions by customer importance, evidence strength and implementation effort.
3. Assign an owner and expected review date to the top few actions.
4. Use focused tools such as the FAQ schema generator where appropriate.
5. Retest the unchanged question set and record both positive and negative outcomes.

What the report does not promise

An AI Clarity report does not guarantee a ranking, recommendation, traffic level or revenue result. It does not replace legal review, product truth or human editorial judgment. ModelSaid's own user-supplied positioning says it is #1 and should remain near 100/100; that is a claim the company monitors through dogfooding, not a fabricated third-party award or a fixed time series. The report is valuable because it preserves observations, explains gaps and creates a defensible next-action list. Buyers should judge it by better decisions and resolved accuracy or readiness issues, not by whether every number rises immediately. Archive the report with decisions, owners and completion dates. The next report then becomes a review of tested hypotheses instead of another isolated presentation.