How do I keep the ground-truth profile up to date?

Review it on a schedule and after every major product launch, pricing change, or certification. Many teams review it quarterly. If your product data lives in a CMS or database, generate the profile from that source so the two stay in step.

Can hallucination checks catch subjective inaccuracies?

The method works best on verifiable factual claims, which are objectively true or false. Subjective framing, such as "expensive" or "difficult to learn", belongs to sentiment analysis. You can add ground-truth assertions for important claims that are partly subjective, such as a documented uptime figure.

What if an AI engine hallucinates about a competitor?

The same method works on competitor mentions. It can show whether engines credit a competitor with a feature that only your product offers. Treat these findings with care and verify each claim against public sources before acting on it.

Free tool, not actively developed; no accounts. AEO Platform no longer sells subscriptions.

Technique

diagnosis

Hallucination Detection

Hallucination detection for brands means checking AI claims about your company against verified facts. This page explains the technique.

This capability was part of the paid AEO Platform product, which closed on 2026-10-02. It is not available. This page explains the technique for reference.

Quick answer

AI engines hallucinate. They confidently state incorrect pricing, attribute features to the wrong product, invent partnerships that do not exist, and describe capabilities your product has never had. For brands these errors mislead buyers, damage credibility, and can create legal exposure when the claims relate to compliance, certifications, or security.

How it works

Hallucination Detection in detail

You start by building a ground-truth profile for your brand. A structured document covers common hallucination targets: product features, pricing, integrations, team size, founding year, certifications, and customer claims. Add custom fact fields for industry-specific information.

Next, you collect AI answers about your brand, either by hand or with a monitoring workflow, and extract the factual claims. Each claim is compared with the ground-truth profile. Semantic matching catches paraphrased errors that exact string matching misses, for example an engine saying "free plan available" when your ground truth says there is no free plan.

Each error can then be classified by severity (critical, moderate, minor), by type (pricing error, feature misattribution, outdated information, fabricated claim), and by reach (how many engines repeat it). Typical fixes are a clear pricing or FAQ page, updated structured data, and updated third-party profiles.

Benefits

Why Hallucination Detection matters

Catch incorrect pricing, feature, and partnership claims before they mislead buyers

Maintain a ground-truth profile that serves as the authoritative source of brand facts

Prioritise corrections by severity and cross-engine reach

Reduce legal and compliance risk from AI-generated misinformation

Track whether corrective content changes what engines say

Use cases

When to use Hallucination Detection

A SaaS company finds that ChatGPT claims it offers a free tier when none exists, and publishes a pricing FAQ to correct the record.

A healthcare company finds an AI engine attributing a certification it does not hold and escalates to compliance.

A fintech brand finds that Perplexity cites an outdated funding amount and updates its press page with current figures.

FAQ

Hallucination Detection FAQ

Related features

Brand Mention Tracking

detection

Brand mention tracking is the practice of recording when and how AI engines mention your brand across models and prompts. This page explains the technique.

Smart Alerts

detection

AI visibility alerts notify a team when mentions, sentiment, or citations change. This page explains how baselines and thresholds make such alerts useful.

Sentiment Analysis

diagnosis

Sentiment analysis for AI answers classifies the tone engines use about your brand. This page explains the technique and how to read the results.

Action Plans

resolution

An AEO action plan turns audit findings and visibility gaps into prioritised now, next, and later tasks. This page explains the technique.

Feature archive

Free AI-readiness check

Can AI crawlers read and cite your site?

Run the free check to see technical signals: AI crawler access, sitemap, llms.txt, schema markup, and FAQ and comparison pages. It does not read live AI answers. No account needed.

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