AI is already answering for you. Is it lying?
Every day, ChatGPT, Gemini, and Perplexity answer questions about your pricing, your hours, your credentials — with or without your input. Hallucination Watch asks the same questions, checks every answer against your verified facts, and drafts the fix before a customer acts on the wrong one.
Checked across every major AI platform & voice assistant
Hallucination Watch checks whether what AI is saying about you is actually true — judged against your own verified facts, not a guess. When it finds a wrong answer, it drafts the fix.
AI doesn't say "I don't know." It guesses — confidently.
A customer asking ChatGPT about your pricing gets an answer either way. The only question is whether it's the right one.
AI fills gaps with guesses
When your own site doesn't have a clear answer, a model still answers — confidently, with something invented, because "I don't know" isn't a satisfying reply to train toward.
Old information looks current
Training data lag and stale third-party citations mean a price you raised two years ago, or a certification you let lapse, can keep showing up as fact.
Customers act on the wrong answer
By the time you find out, they've already decided — booked at the wrong price, assumed a certification you don't have, or picked a competitor AI described more confidently.
Judged against your truth, not a guess.
Every answer is checked against real ground truth — the facts you set, and public authoritative sources when you haven't — then ranked by how much it could actually cost you.
Your verified facts
Pricing, address, hours, founding year, certifications, and any claims you've flagged as things that should never be said — the canonical truth you set.
Public authoritative sources
Your own site description, Wikidata, and Wikipedia get cross-checked automatically when you haven't set a fact yourself.
Fabricated specifics
A named statistic, award, certification, or person with no supporting source anywhere — the kind of confident invention a customer has no way to catch.
Cross-engine consistency
The same question, asked of all 10 engines, so you see exactly where they disagree with you — and with each other.
Severity, not noise
Opinions and marketing adjectives are never flagged. Only checkable facts, ranked high/medium/low by how much they could actually cost you.
Trend over time
Every run appends to your history, so you can watch hallucinations drop as you publish corrections — not just a one-time snapshot.
Most "AI monitoring" cries wolf. This one is judged.
A tool that flags every off-sounding sentence trains you to ignore it. Hallucination Watch is built the opposite way: when in doubt, it does not flag — so when it does flag something, it's real.
How a noisy tool flags things
- Keyword-matches anything that "sounds" negative or off-brand.
- Flags opinions and marketing language as if they were facts.
- No ground truth to check against — just vibes.
- Alert fatigue sets in, and real issues get ignored with the noise.
How Hallucination Watch decides
- Judged against your truth. Every answer is checked against the canonical facts you verify — not a keyword list.
- When in doubt, it doesn't flag. The instruction to the judge is explicit: unverifiable claims and opinions are left alone.
- Only specific, checkable facts. A wrong price, a fabricated certification, a contradicted founding year — not "sounds a bit off."
- Severity that means something. High/medium/low reflects real cost — pricing and compliance surface first.
One scan. Every engine. Every answer checked.
This is the run happening — the kind of fact-check no single person could do by hand across ten AI engines. Watch what one scan actually covers.
"Yes — ISO 9001 certified since 2021."
✗ False"I can't find a verifiable certification claim."
Not flagged"No — no certification is listed on their site."
✓ TrueWhat one run hands you.
- Every answer, not a guess. 10 questions × 10 engines = up to 100 real answers, checked against your own facts — on the sample above, 2 wrong.
- A judge that errs conservative. Opinions and marketing language are never flagged — only checkable facts that could mislead a customer.
- A fix you can publish today. Every wrong answer gets a drafted correction, grounded only in your verified truth, ready to ship.
- The score itself is free. Top 3 wrong answers unlock on AI Pulse ($499/mo); the full monitor with drafted corrections unlocks on AI Radar ($899/mo) and up.
Hoping vs. knowing.
| What you get | 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/mo (Top 3) · full monitor at $899/mo |
Ask. Judge. Fix. Re-prove.
Ask
Real, checkable questions a customer would ask — pricing, hours, credentials, history — drafted from your own canonical facts, plus any custom questions you add.
Judge
Every engine's answer is fact-checked against your verified truth and public authoritative sources, conservatively — opinions and marketing language are never flagged.
Fix
Every wrong answer gets a drafted correction, grounded only in your verified facts, ready to publish into your schema, llms.txt, and site content.
Re-prove
Re-ask the exact question across engines to see which ones picked up the fix — typically within two to four weeks.
The vocabulary of AI accuracy.
The terms your Hallucination Watch report uses — defined plainly.
- Hallucination AI
- A confident but false or fabricated statement an AI model makes — a wrong price, a fake certification, an invented fact — presented as though it were true.
- Canonical facts
- The verified ground truth you set for your own brand — pricing, address, hours, founding year, certifications, and any 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 your 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 AI engines now answer correctly.
- Severity high/med/low
- How Hallucination Watch ranks a wrong answer's risk — high covers pricing, legal/compliance, and violated "never claims," so the worst issues surface first.
Questions about Hallucination Watch.
What is Hallucination Watch?
Hallucination Watch is AI Syndicate's AI-accuracy monitor. It drafts real, checkable questions about your brand — pricing, hours, credentials, history — asks them across every major AI engine, and judges each answer against your verified facts. Every wrong answer gets a drafted, publish-ready correction.
How is this different from generic brand monitoring?
Generic monitoring watches for mentions. Hallucination Watch checks whether what AI is actually saying about you is true — judged against the canonical facts you set (pricing, address, hours, founding year, certifications) and public authoritative sources when you haven't. It's built to be conservative: opinions, marketing language, and anything unverifiable 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 specific claim that contradicts your own verified truth or public authoritative data. Nothing else gets flagged.
Will it flag opinions or marketing language?
No. The judge is deliberately conservative — when in doubt, it does not flag. Subjective claims ("the best," "industry-leading") and anything that can't be verified either way are left alone. Only specific, checkable facts that could mislead a real customer get flagged.
How does the fix actually work?
You can't force an AI engine to retract a statement, so the fix isn't an email to a provider — it's publishing the truth in the places AI actually reads. Every wrong answer gets a drafted correction, grounded only in your verified facts, ready to publish into your schema, llms.txt, and site content — becoming the freshest, strongest signal the next answer draws from.
How long until a correction shows up in AI answers?
It varies by engine and source. Re-running the exact question after publishing typically shows movement within two to four weeks; corrections that also update your Google Business Profile or Bing listing can register within a couple of weeks. Hallucination Watch re-asks the same question so you see exactly which engines picked up the fix.
Is the free scan really free?
Yes. Running your Hallucination Watch scan costs nothing — you get your accuracy score and a preview of what's wrong. The 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, so a full run can check up to 160 individual answers.
Can I add my own questions?
Yes. Any custom questions you submit run first, ahead of the drafted battery, so you can target the exact claims you're worried about.
Find out what AI is saying about you — before a customer does.
It's free, it takes a minute, and it's the one check that tells you whether AI is telling the truth about your business.