Use case · Correction
The AIs repeat something false about you. Now what?
A shutdown you never had, an old price, a namesake's story told as yours: Epovest turns the rumor into a dated record, finds the pages feeding it, and measures until the error stops coming back.
Views from the app. Your figures replace the sample at the first survey.
An error has sources, and sources can be worked
Engines repeat pages. A correction episode starts by putting the faulty answer on the record, dated and quoted, and ends when the checks stop finding it. In between, every gesture targets a page: yours to realign, someone else's to get corrected or outweighed by fresher ones.
What you measure
The faulty answers, on the record
Every answer that carries the error is archived in full, dated, engine by engine: your evidence file builds itself.
The sources behind the error
The pages each engine cites next to the faulty passage: where the story actually comes from.
Extinction per engine
Check after check, which engines still repeat the error and which have moved on.
The episode, dated end to end
First observation, every fix, last faulty answer: the whole episode stays readable after it closes.
The recipe
How to correct a wrong AI answer with Epovest
The full working guide for this use: put the error on the record, trace it to its sources, fix in the right order, and measure extinction engine by engine.
Put the error on the record
Ask the engines the questions that surface the error, phrased the way a customer would stumble on it. The deliverable of the first check is a dated, quotable record of the faulty answers.
"Is [your brand] still in business?"
"What does [your product] cost?"
"Who runs [your brand] today?"
Two or three prompts aimed at the fact are enough; add one neutral prompt about your name to see how far the error spreads beyond its trigger. Daily cadence, all four engines: an episode needs a dense series more than a long one.
Trace the error to its bibliography
Open each faulty answer: the source cited next to the wrong passage names the page feeding it.
The Atlas, narrowed to this project, assembles those pages into the episode's bibliography: an old article, a forum thread, an outdated directory entry, a namesake's page. Rank them by the authority of the engine that repeats the error most: that order is your work order, heaviest feeder first.
Fix where you have the final say
The true fact is written once, in the canon: the founding date, the current price, who runs what, the line that separates you from the namesake.
Then align the pages you control: the surfaces registry runs you through your site, your llms.txt, your profiles and listings, checklist by checklist, and dates each alignment. An engine that rereads your pages must find the true fact stated plainly everywhere you speak, with no page of yours left contradicting you from within.
Obtain where someone else has the final say
The page feeding the error is rarely yours. Record it as a corroboration and work it from there.
The register carries a request channel for each page: the editor to write to, the directory's correction form, the platform's report path. Ask for the fix, date the request, and arm weekly monitoring on the page: you will know the week the passage changes. When a page will not move, outweigh it: obtain fresher pages that state the true fact, recorded and dated in the same register.
Measure the extinction, then close
The daily series answers the question the episode is about: which engines still repeat the error?
Read it engine by engine: one clears in days, another holds to its source for weeks. An engine gone quiet on the error for two checks in a row is cleared; when the last one moves on, the episode closes. Drop the cadence or pause the tracker: the record stays, dated end to end, and reads as your proof of diligence long after.
Worked example
An engine says you shut down
A prospect mentions it: an assistant told them you closed two years ago. Day one: three prompts on the record, daily, all engines; two repeat the closure and both cite the same liquidation notice of a namesake. Day two: the canon states the distinction, your surfaces realign, the notice enters the corroborations register with a correction request and weekly monitoring. The next checks watch the error die: one engine clears within the week, the other after its source edits the page. The episode closes with a dated file: who said it, what fed it, what fixed it.
With your AI assistant
Your AI assistant runs this recipe with you
Connect Epovest to the assistant you already use, one-click connector or API key. It creates trackers, reads the results and keeps the registers with you; a payment only ever happens with your approval.
The instruction to give it
Connect to Epovest and open a correction episode on [the wrong fact AIs repeat about me]: three prompts that surface it, daily on all engines. Trace the cited sources, set up the fixes with me, and tell me at each check which engines still repeat it.
$0.10
per prompt, per engine, per check
Pricing
Whatever you configure, the unit never changes. Your total shows live in the configurator before anything runs; you start whenever you want, from a $10 top-up. No subscription: only the checks that run are debited.
The cadence follows the episode
Run daily while the correction is hot, come back to weekly once the answers are clean: the change opens a new version of the tracker and the series carries on, one record from first alert to closure.
The other use cases
Make AIs recommend you
Create a tracker in minutes: your prompts, your engines, your cadence. First checks within 24 to 48 hours.
No subscription. Credits from $10, valid 12 months. Pause anytime: the history stays yours.