PLATFORM / TRUTH MONITOR
When AI Gets Your Brand Wrong, Be the First to Know
Truth Monitor audits every sentence answer engines produce about your brand at the level of individual facts: a wrong price, an outdated feature list, a confused product name, an incorrect return policy. When a drift is detected it traces the source, opens the correction as a Workflow Agent task and tracks the fix until it lands back in the answer.
THE CHALLENGE
Models Talk About Your Brand Without You in the Room
Wrong facts surface at the moment of purchase
A model states an outdated price, a discontinued feature or the wrong ownership — exactly when a buyer asks. Nobody on your team hears it happen.
The source is invisible
When AI gets your brand wrong, the error came from somewhere: an old page, a stale directory, a third-party post. Finding which one by hand is archaeology.
“You cannot fix an LLM” is a myth that costs you
You cannot patch the model, but you can fix the sources it reads. Most wrong claims trace to correctable pages.
Damage compounds silently
A wrong claim repeats across thousands of conversations before anyone notices. The gap between first error and first alert is the whole cost.
HOW IT WORKS
From Claim to Correction in Four Steps
Extraction
Factual claims are parsed out of every answer that mentions your brand: numbers, dates, policy sentences, product attributes.
Comparison
Claims are checked against your approved source-of-truth set: price lists, policy pages, product data.
Root Cause
When a drift is found, the source the model cited is traced — usually an old blog post, a third-party listing or an expired campaign page.
Fix and Confirm
The correction opens as a Workflow Agent task; after it ships, the same prompts re-run until the claim is confirmed fixed.
ALERT TO FIX
From Wrong Claim to Re-verified Correction
Truth Monitor asks the models about your brand on schedule, diffs the answers against your fact sheet, and when a claim drifts, opens an alert with the probable source attached. The fix flows through the same pipeline as everything else.
Detect
Scheduled brand-fact prompts across engines
Alert
Slack alert with the claim and the diff
Trace
Probable source page identified
Fix
Correction drafted via Workflow Agent
Re-verify
Claim re-tested until it reads correct
WHAT IS WATCHED
Your Fact Sheet, Under Continuous Test
Pricing, product names, ownership, locations, claims you legally must control — you define the facts, the monitor keeps asking. Sensitive categories get review notes so corrections clear compliance first.
- You control the fact sheet being tested
- Per-engine status for every fact
- History of drift and correction per claim
truth monitor — fact status
DRIFT TYPES
The Four Most Common Drifts and What They Cost
Distribution of drifts detected across enterprise customers in the first 90 days. Sample: 38 brands.
WHY NOW
A Wrong Answer Costs More Than No Answer
The Only Impression in a Zero-click Era
When users decide without visiting your site, the sentence AI produces is your only storefront. If it is wrong, you never get the chance to correct it.
Evidence for Legal and Compliance
Every drift is archived with screenshot, model, date and source. In regulated industries it goes straight into the audit file.
A Category First
Fact monitoring is a new layer for the category; measurement tools report the drift, Truth Monitor delivers the fix and confirms it.
FAQ
Truth Monitor, Asked Directly
What counts as “wrong”?
Anything that contradicts the fact sheet you define: prices, availability, ownership, claims. You set the ground truth; the monitor tests against it.
How is the source found?
Cited sources in answers, crawl data and content matching narrow the claim to its probable origin — usually a specific page you or a third party can correct.
Can you guarantee the model corrects itself?
No honest tool can. What we do: fix the sources, then keep re-testing. Models refresh on their own schedules — corrections typically propagate as they re-crawl.
Which engines are monitored?
The engines in your plan — ChatGPT, Gemini, Perplexity, Claude and Copilot among them — each tested separately, because they drift separately.
Where do alerts arrive?
Slack today, with each alert carrying the claim, the engine, the diff and the traced source.
What about legally sensitive claims?
Facts can be flagged as sensitive; their corrections carry a review note and wait for approval before anything ships.
How often are facts re-tested?
On a scheduled cadence per fact, with drifted claims re-tested more frequently until they stabilise.
Which plan includes it?
Truth Monitor ships with Growth and above.
For the first time, legal knew before marketing: Truth Monitor caught a model citing our old return policy, and the fix reflected in answers within 11 days.
Enterprise customer, finance General Counsel
See Where Your Brand Stands Today
The free audit takes about four minutes to set up. The result screen shows your score and the first three fixes.