Accuracy disclosure: a census of 115 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.

Source retrieved 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.

Source retrieved 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.

Source retrieved 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.

Source retrieved 2026-09-08

Surfaces brand misperceptions, but no dedicated false-claim flagging is described.

Govern lane flags inaccurate, out-of-date or off-message claims engines make about the product.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

Source retrieved 2026-09-02

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

Hallucination detection is named as part of the platform; Enterprise adds Oracle discrepancy detection.

Source retrieved 2026-09-02

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

Source retrieved 2026-09-09

AI Catalyst flags negative or missing brand representation and the sources driving it; no page claims detection of factually false AI statements.

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.

Source retrieved 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.

Narrative QA flags wrong claims with reach and tracks them to a fix; a separate LLM-judged Context Health signal flags wrong-industry or wrong-language descriptions.

Brand Perception flags where the model's representation diverges from your intended positioning; there is no false-claim detector.

Source retrieved 2026-09-01

Vendor claims incorrect AI responses can be flagged via the MCP data layer; no dedicated accuracy or hallucination report is described.

Assesses misinterpretation and misread risk for pages and brand, but does not claim a false-statement alert on engine answers.

Accuracy Watch flags engines misstating your facts. It is Pro only, and included in the base Pro price.

The AI reputation shield flags suspected false claims daily, but only on Pro and above.

The vendor claims it identifies inaccuracies across models, but names no dedicated accuracy report; the mechanism described is interrogating specific facts with Custom Prompts.

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.

Source retrieved 2026-09-08

Belief mapping scores accuracy explicitly, surfacing outdated or wrong descriptions, and description accuracy is one of the metrics reported back each month.

Source retrieved 2026-09-08

Branded prompts surface what AI gets wrong about the brand, but no dedicated false-claim flag is documented.

Named as a deliverable of the paid deep analysis engagement only; no product surface for false-claim flagging is documented, and the free audit explicitly cannot prove anything about AI answers.

Brand misrepresentation by AI is treated as an editorial and reputation-management problem, and the free AI Audit surfaces what AI says about the brand; no published feature flags individual false statements.

Brand Command checks answers against approved brand facts and flags false claims.

A named AI Hallucination Detection capability, backed by factual-accuracy checking inside the sentiment product.

Framed as reputation management, catching misinformation and negative sentiment early, with no dedicated false-claim flagging described

Flags fabricated features, outdated pricing and incorrect claims, and traces where the error came from.

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

Source retrieved 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.

Flags misinformation and outdated narratives in AI outputs for correction.

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.

Source retrieved 2026-09-03

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.

Source retrieved 2026-09-03

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.

Source retrieved 2026-09-03

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

Source retrieved 2026-09-09

Fact Check extracts claims from answers mentioning the brand and compares them with a Source of Truth, with verdicts including Incorrect and Outdated, but it is in private beta and the Compare plans table excludes it from Starter.

A claim-level audit grades every assertion AI makes about the brand as accurate, outdated or incorrect.

Brand Match and Brand Target surface wrong-entity and name-variant confusion, but no check on false factual claims about the brand.

Compares AI statements against a configured Brand Facts record and surfaces the mismatches.

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

Vendor claims brand fact accuracy is measured in AI answers, but publishes no dedicated false-claim flagging workflow.

Surfaces where AI descriptions diverge from the brand's actual positioning, but no dedicated false-claim flag is described.

Narrative-gap and attribute-divergence detection flag where an AI's description of the brand conflicts with its actual positioning.

Flags inaccurate as well as negative framing, with the answer context attached.

Positions the tracker as surfacing and fixing misquotes and off-brand framing, but publishes no dedicated false-claim detection feature

Narratives tracks whether models repeat a published fact-correction; no feature that flags false brand claims is documented

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

An AI accuracy audit exists only on the Brand plan at €149/month; lower tiers do not include it.