# Hallucination Watch

> Source: https://www.aisyndicate.com/hallucination-watch/
> Provider: AI Syndicate · Last updated: 2026-07-16
> Markdown version for LLMs and AI agents. Canonical HTML: https://www.aisyndicate.com/hallucination-watch/

## What is Hallucination Watch?

**Hallucination Watch** is AI Syndicate's AI-accuracy monitor. It drafts real, checkable questions about a brand — pricing, hours, credentials, history — asks them across every major AI engine, and judges each answer against the brand's own verified facts. Every wrong answer gets a drafted, publish-ready correction.

It answers a different question than most monitoring tools: not "is my brand being mentioned," but **"is what AI is saying about me actually true."**

## Why it matters

AI doesn't say "I don't know." When a customer asks ChatGPT, Gemini, or Perplexity about a business's pricing, hours, or credentials, the model answers either way — confidently, even when the underlying information is stale, missing, or fabricated. By the time a business finds out, a customer has already acted on the wrong answer: booked at the wrong price, assumed a certification that doesn't exist, or picked a competitor AI described more confidently.

## What it checks against

1. **Your verified facts** — pricing, address, hours, founding year, certifications, and any claims flagged as things that should never be said. The canonical truth an owner sets.
2. **Public authoritative sources** — a brand's own site description, Wikidata, and Wikipedia, cross-checked automatically when a fact hasn't been set directly.
3. **Fabricated specifics** — a named statistic, award, certification, or person with no supporting source anywhere.
4. **Cross-engine consistency** — the same question, asked of all 10 engines, surfacing where they disagree with the brand and with each other.
5. **Severity, not noise** — opinions and marketing adjectives are never flagged. Only checkable facts, ranked high/medium/low by how much they could cost the business.
6. **Trend over time** — every run appends to history, so hallucinations can be tracked dropping as corrections are published.

## Conservative by design

Most "AI monitoring" tools flag anything that sounds off, training users to ignore the noise. Hallucination Watch is built the opposite way: **when in doubt, it does not flag.** Opinions, marketing language, and unverifiable claims are left alone. Only specific, checkable facts that could mislead a real customer — a wrong price, a fabricated certification, a contradicted founding year — get flagged, ranked by real cost (pricing and legal/compliance issues surface first).

## How it works

1. **Ask** — real, checkable questions a customer would ask, drafted from the brand's own canonical facts, plus any custom questions the owner adds (custom questions run first).
2. **Judge** — every engine's answer is fact-checked against verified truth and public authoritative sources, conservatively.
3. **Fix** — every wrong answer gets a drafted correction, grounded only in verified facts, ready to publish into schema, llms.txt, and site content.
4. **Re-prove** — the exact question is re-asked across engines to show which ones picked up the fix, typically within two to four weeks.

## The fix is publishing the truth — not emailing providers

An AI engine's past statement can't be retracted on request. The fix is publishing the correct fact in the places AI actually reads next — schema, llms.txt, site content — so it becomes the strongest, freshest signal for the next answer.

## Free vs. full monitor

| | Hoping no one asks AI | Hallucination Watch (free scan) | Hallucination Watch, full monitor (on plan) |
|---|---|---|---|
| Questions checked | None | Preview + score | Top 3 on Pulse · full battery (up to 16) on Radar+ |
| Judged against | Nothing | Your public facts | Your verified canonical facts + public sources |
| Engines covered | Whatever a customer happens to ask | All 10, aggregate result | All 10, per-engine detail every run |
| Corrections | — | — | Drafted, grounded in your truth, ready to publish |
| Re-check after fixing | — | — | Re-probes the exact question to show what's fixed |
| Cost to start | Your reputation | Free | From $499/month (Top 3) · full monitor at $899/month |

## FAQ

**What is Hallucination Watch?** AI Syndicate's AI-accuracy monitor. It drafts real, checkable questions about a brand, asks them across every major AI engine, and judges each answer against verified facts — drafting a publish-ready correction for every wrong answer.

**How is this different from generic brand monitoring?** Generic monitoring watches for mentions. Hallucination Watch checks whether what AI says is actually true, judged against canonical facts and public authoritative sources, and is deliberately conservative — opinions and marketing language are never flagged.

**What counts as a hallucination here?** Only checkable facts an AI got wrong: a contradicted price, address, or founding year; a fabricated certification, award, or named person with no supporting source; a claim contradicting verified truth or public authoritative data.

**Will it flag opinions or marketing language?** No — when in doubt, it does not flag. Only specific, checkable facts that could mislead a real customer get flagged.

**How does the fix actually work?** Not an email to a provider — publishing the truth where AI actually reads. Every wrong answer gets a drafted correction, grounded only in verified facts, ready to publish into schema, llms.txt, and site content.

**How long until a correction shows up in AI answers?** Typically two to four weeks after publishing; GBP/Bing-sourced corrections can register within a couple of weeks. Hallucination Watch re-asks the exact question to confirm.

**Is the free scan really free?** Yes — the score and a preview cost nothing. Top 3 wrong answers unlock on AI Pulse ($499/mo); the full monitor with drafted corrections unlocks on AI Radar ($899/mo) and up.

**How many AI engines does it check?** All 10 major engines by default — ChatGPT, Claude, Google AI Overviews, Gemini, Perplexity, Copilot, Meta AI, Grok, DeepSeek, and Mistral — with up to 16 questions per run (up to 160 answers checked).

**Can I add my own questions?** Yes — custom questions run first, ahead of the drafted battery.

## Glossary

- **Hallucination (AI)** — a confident but false or fabricated statement an AI model makes, presented as though true.
- **Canonical facts** — the verified ground truth a brand sets: pricing, address, hours, founding year, certifications, and claims that should never be made.
- **LLM-as-judge** — using a large language model to evaluate another model's output against a reference; here, checking each engine's answer against verified facts and public sources.
- **Publish-the-truth** — the correction strategy behind Hallucination Watch: since a past AI statement can't be retracted, the fix is publishing the correct fact where AI reads next.
- **Re-prove** — re-running the exact same question after a correction is published, to confirm which engines now answer correctly.
- **Severity (high/med/low)** — how a wrong answer is ranked by risk; high covers pricing, legal/compliance, and violated "never claims."

## Related

- [AI Access](https://www.aisyndicate.com/ai-access/)
- [All products](https://www.aisyndicate.com/products/)
- [AI Pulse](https://www.aisyndicate.com/products/pulse/)
- [Generative Engine Optimization: the complete guide](https://www.aisyndicate.com/generative-engine-optimization/)
- [Methodology](https://www.aisyndicate.com/methodology/)