Accuracy disclosure: a census of 124 listings

Flagging false statements is a stated part of the monitoring service, and citation accuracy is one of the three numbers carried in the monthly report.

Checked 2026-09-10

Branded query testing is said to expose misrepresentation, but there is no dedicated false-claim flag, alerting or correction workflow described anywhere.

Checked 2026-09-10

No feature that flags a false statement about the brand; the docs name responding to misinformation as a persona use case, and the Details view exposes the full AI response text behind each prompt.

Accuracy of what engines say is claimed as something the analytics assess, but no alerting, flagging surface or correction workflow for false statements is documented anywhere on the site.

Checked 2026-09-10

Tracking flags a wrong fact appearing in an answer as movement worth alerting on, and the Action Engine routes contradicted facts and misdescribing profiles into entity corrections.

Checked 2026-09-08

The perception view is said to surface misperceptions, but the vendor documents no dedicated flag, alert or workflow for false statements about the brand.

Checked 2026-09-17

Govern lane flags inaccurate, out-of-date or off-message claims engines make about the product.

Accuracy of description is scored and a Brand Facts verification queue exists to pre-empt wrong basics, but no dedicated false-claim flag or alert is published.

Checked 2026-09-02

You can read every stored response and fire your own classification follow-up, but no automatic false-claim flagging is described.

Oracle flags false claims against your verified facts, but it needs at least 25 verified Knowledge Base facts and is sold as an Enterprise capability.

Checked 2026-09-20

Brand-safety tooling flags misleading AI-generated statements about the brand and raises real-time alerts with suggested corrective action.

Checked 2026-09-09

The platform flags negative and outdated narratives AI repeats about a brand, but never claims to detect factually false statements as such.

Checked 2026-09-11

The scanner surfaces engine answers that are off message and flags negative or risk language, and the vendor advises escalating persistent red flags, but scoring is lexical overlap and a tone dictionary, so it detects wrongness of positioning rather than verifying factual claims.

Checked 2026-09-08

Monitoring records whether the business is misdescribed, but no dedicated false-claim flag or alert is documented; the vendor attributes hallucination detection to other tools in its own comparison table.

A dedicated alert type fires when engines state something inaccurate or misleading about the brand, and it is graded urgent with a documented response playbook.

Checked 2026-09-13

Brand perception tests whether the model's account of the brand matches its real positioning and flags thin or conflicting signals, but no feature marks a statement as false.

Checked 2026-10-08

There is no dedicated false-claim detector; the vendor positions incorrect AI answers as something you spot through full response exports, sentiment statements and their sources.

Checked 2026-10-06

Brand Crisis Management watches for factually wrong or negative statements about the brand in answers and traces each one back to the question, model and cited source that produced it.

Checked 2026-09-15

Daily claim extraction flags cross-engine conflicts and suspected falsehoods and drafts a correction, but the shield starts at the Pro plan.

Checked 2026-09-13

The vendor frames distorted or outdated AI claims as a risk it monitors through accuracy and sentiment tracking, but publishes no dedicated false-claim flagging feature.

Checked 2026-09-24

Custom Prompts lets you interrogate models on pricing or feature claims to surface factual errors, but no automated flag for false statements is documented.

Checked 2026-09-12

Catching misinformation is named as a use case of sentiment monitoring, and a Fact Check row is sold as an add-on on every tier with no published description or price.

Checked 2026-09-08

Wrong or weak AI beliefs are surfaced and remediated as a named programme, but it is positioned as positioning correction rather than monitoring for false factual claims.

Checked 2026-10-16

Branded prompts and sentiment surface where a model misdescribes the brand, but the vendor documents no dedicated false-claim flag or alert.

Checked 2026-10-05

Accuracy Watch flags engines stating your facts wrongly, but it is withheld from the $29 Starter plan and only ships with Pro, Managed and Agency.

Checked 2026-09-14

Citation accuracy is measured on Google's surfaces only; nothing claims flagging of false brand statements on the other engines.

Checked 2026-09-14

A mention can be flagged as factually wrong as part of sentiment, but there is no dedicated hallucination report and the flag exists only where monitoring runs.

Checked 2026-09-14

Outdated services and wrong locations in AI answers are named as something the measurement surfaces, but no dedicated flagging or correction workflow is described.

Checked 2026-10-03

The agency offers to establish what AI says about a brand and publishes a manual playbook for finding wrong or outdated AI descriptions, but no automated false-claim flagging feature is documented.

Checked 2026-09-14

Brand Command measures every answer against facts your team approves and flags false claims, ranking corrections by how far the error reaches.

Checked 2026-09-15

Hallucination detection is listed as an included feature of the entry AI Visibility plan and has its own feature page for flagging false claims.

Checked 2026-10-07

Misinformation is caught through sentiment monitoring of the full captured answer rather than a dedicated false-claim flag, so the reader does the judging.

Checked 2026-10-09

Accuracy Tracking flags responses containing invented or outdated facts about the brand, categorises them and traces where the error came from.

Checked 2026-10-10

Accuracy scoring is the vendor's stated differentiator: the audit checks whether what AI says is true and flags wrong pricing or misattributed features.

Checked 2026-09-03

The vendor frames monitoring AI descriptions as the way to catch wrong hours, locations or descriptions, but publishes no dedicated false-statement flag.

Detecting misinformation and outdated claims in AI answers is presented as a named use, with early risk detection through sentiment and trend analysis.

Checked 2026-09-18

Wrong claims made by assistants are traced back to the page being quoted and a fix is supplied; drafts are also fact-screened before publication.

Checked 2026-10-14

Accuracy and misinformation monitoring is claimed once, as a Brand Protection benefit card; no dedicated feature, alert or false-claim report is described anywhere, and the free report frames the same idea as blind spots.

Checked 2026-09-03

A dedicated workstream tracks inaccurate or outdated AI claims about the product, traces them to the source and pursues corrections at that source.

Checked 2026-09-28

Accuracy of the model's description is an explicitly monitored metric, and the framework names hallucinated solution mapping as a defect the MOFU work targets.

Checked 2026-09-03

Checks AI claims about the brand against facts you supply and marks each one Contradicted or Supported, then turns wrong ones into fixes.

Checked 2026-09-29

Brand Perception carries a Fact-checking tab that measures AI claims about you against facts you supply, and the marketing page frames the same feature as spotting false statements.

Checked 2026-09-03

The vendor frames accuracy of AI answers as an objective of the entity and PR work, but publishes no dedicated false-claim detection or alerting deliverable in the plan table.

Checked 2026-09-29

FactCheck flags false claims AI makes about the brand and points at the sources producing them, with follow-up agent templates.

Checked 2026-09-09

Fact Check, the feature that checks accuracy of AI statements about the brand, is marked Beta and is not included on the entry Starter plan.

Checked 2026-10-10

Every assertion an engine makes about the brand is captured and graded for accuracy, which is how the product surfaces false or stale AI claims rather than only absence of mentions.

Checked 2026-10-11

Brand-confusion failures are an explicit target of the entity and match analysis, but the vendor describes misspellings, wrong categories and merged companies rather than false factual claims.

Checked 2026-10-11

The audit compares each engine's description against configured Brand Facts and flags misstatements such as a wrong category.

Checked 2026-10-12

It surfaces negative themes per model and the reasoning behind them, but the vendor's own workflow puts the judgement of what is false on the user rather than flagging factual errors itself.

Checked 2026-09-30

Claim accuracy checks what engines assert about the brand against the facts and traces wrong claims to their source

It collects the facts engines state about the brand and carries a verification status, but no dedicated misinformation alerting is documented on the plan pages.

Checked 2026-10-13

Brand Performance surfaces the exact wording and attributes AI uses so you can judge accuracy, but Semrush documents no dedicated flag for factually false claims about the brand.

Checked 2026-09-18

Owner-declared business facts are stored as ground truth and used to spot AI answers that contradict them, though the vendor markets no separate hallucination report.

Checked 2026-10-03

It stores the wording engines use and surfaces where platforms contradict each other or place the brand in the wrong category, but no dedicated false-claim alert is described, and sentiment sits behind Starter.

Checked 2026-09-15

Inaccurate framing surfaces through the answer text and its sentiment read, which the vendor markets as spotting misinformation, but there is no dedicated false-claim detector or alert described anywhere.

Checked 2026-09-17

Sentiment and mention data are pitched explicitly at finding misquotes and inaccurate AI narratives about the brand so they can be corrected.

Checked 2026-10-09

A dedicated Accuracy report grades answers as false when a claim contradicts your site or a verified record, though it covers three assistants rather than all eight.

Checked 2026-09-16

The full AI response is stored and readable so you can spot false claims yourself; there is no automated hallucination flag or alert.

Audits test whether assistants describe the brand accurately, and a dedicated AI accuracy audit is a Brand-plan feature rather than a standard one.

Checked 2026-09-18