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Quote Integrity Verification: Protecting Your Brand from AI Hallucinations
•Erik Svilich, Founder & CEO | Encypher | C2PA Text Co-Chair

Quote Integrity Verification: Protecting Your Brand from AI Hallucinations

When AI systems claim 'According to the New York Times...' but the quote is wrong, your brand takes the hit. Here's how quote integrity verification protects publisher reputation.

#AIHallucination#QuoteVerification#BrandProtection#ContentAuthenticity#Trust

By: Erik Svilich, Founder & CEO | Encypher | C2PA Text Co-Chair

"According to the Associated Press, the president announced..."

"As reported by Reuters, scientists discovered..."

"The Wall Street Journal stated that..."

These attributions appear constantly in AI-generated content. 󠇟󠇠󠇡󠇢󠄃󠇄󠄩󠄬󠆞󠇟󠄳󠇌󠅺󠆎󠄋󠆡︆󠆤󠇖󠆽󠇓󠇩󠆼󠄀󠅐󠄒󠇒󠇠󠆕󠅼󠇁󠆮󠆴󠅻󠅄󠇝󠅌󠅄󠅵󠇢󠇨󠄋󠆓󠄒They lend credibility, suggest authoritative sourcing, and imply factual accuracy. 󠇟󠇠󠇡󠇢󠄊󠄘󠇘󠆏󠄖󠇊󠄴󠅬󠆏󠆩󠇖󠄃󠅾󠆍󠄈󠆫󠄨󠅑󠆯󠆎󠅒󠇉󠆸󠇂󠆆󠅮󠄸󠅀󠇅󠅹︋󠆌󠇉󠄄󠇙󠆑󠆝󠇆󠄯󠆱There's just one problem: **AI systems frequently get these quotes wrong. **

󠇟󠇠󠇡󠇢󠄣󠆚󠇨︍󠄗󠆇󠄳︁󠆐︉󠄲󠆘󠄲󠇂󠅢󠄥󠇓︆󠆿󠆹󠇙󠆫󠄜󠇂󠇫︈󠅅󠅐󠇮󠇅󠇈󠅷󠅻󠆁󠆆󠆾󠄮󠇝󠆜󠆺## The Hallucination Problem

Large language models don't retrieve information—they generate it. 󠇟󠇠󠇡󠇢󠆚󠅞󠇬󠄑󠄀󠇀󠄰󠄊󠅺󠆂󠇠󠄐󠆧󠇋󠄨󠅄󠄈󠅋󠇌󠄄󠆾󠇢󠄌󠅠󠆕󠇎󠅀󠇭󠅿󠄃︂󠅧󠄛󠇕󠇮󠆊󠅙󠇊󠇧󠄱When an AI attributes a statement to a news organization, it's not pulling from a database of verified quotes. 󠇟󠇠󠇡󠇢︁︎︃󠄾󠅰󠅊󠄾󠅭󠆋󠆡︃󠇨󠇅󠇕󠅌󠄵󠇁󠄶󠆂󠅹󠆨󠅳󠄿󠆌󠅊󠆈󠄢󠆁󠅓󠄑󠄎󠆶󠅁󠄙︋󠄡󠅲󠆚󠅓󠆵It's predicting what words should come next based on patterns learned during training. 󠇟󠇠󠇡󠇢󠅨󠆅󠆴󠇭󠄶󠅀󠄼󠆈󠆙󠇪󠇀󠄐󠄛󠇆󠆘󠅎󠇮󠆖󠄈󠄞󠇒󠅓󠇌󠄈󠅘󠄮󠅃󠆦󠅳󠅤󠅻󠇕︌︂󠆴󠆗󠇦󠆐󠄿󠆻This leads to several types of errors:

Fabricated Quotes 󠇟󠇠󠇡󠇢󠇓󠇗󠅧󠆺󠄖󠆱󠄻󠇄󠅷󠄾︀󠆹︈󠆪󠅰󠇊󠅽︁︃︊󠄸󠆐︆󠄓󠄾󠄃󠆯󠅦󠅝︂󠆓󠄠︉󠇮︈󠆴︅󠆝󠄳󠇉The AI generates a quote that was never published. 󠇟󠇠󠇡󠇢󠅸󠄡󠅪󠆣󠇜󠅹󠄲󠄫󠅺󠅩󠇯󠄔󠆩󠄾󠆣󠅑󠅊󠇀󠇯󠄋󠆂︈󠆹︃󠅼󠅟󠄑󠅆󠄡󠇐󠆝󠇈󠄗󠆌󠅱󠅻󠆄󠅝󠅑󠄶The attribution looks real, but the content is entirely invented. 󠇟󠇠󠇡󠇢󠆔󠆓︌󠅤󠆩󠄂󠄾󠄜󠆞󠆁󠅩󠄀󠇂󠄋󠅻󠄓󠆳󠅊󠄪󠄉󠇎󠅾󠅐󠆤󠇜󠇡󠆀󠇩󠄌󠅿󠇆󠅯󠆡󠇛󠆉󠅽󠆑󠅝󠆾󠆭Example:

"󠇟󠇠󠇡󠇢󠅏󠇗󠆡󠄍󠆆󠅻󠄻󠅙󠆍󠇔󠄈󠆷︅󠄌󠄼󠆤󠅾󠆻󠇧󠅄󠅟󠆚󠄔󠆊󠅤󠆵󠅀󠄳󠆦󠇨󠆣󠄸︃︊󠄺󠆇󠇫󠆆󠆭󠇒According to the New York Times, the company's revenue increased by 47% in Q3. "

*󠇟󠇠󠇡󠇢󠅟︀󠅭󠅯󠇑︄󠄺󠄩󠆖󠄟󠄷󠆕󠇞󠅀󠄛󠄧󠅤󠄄󠅗󠆺󠄏󠇌󠄧󠇂󠄏󠆼󠇘︇󠇀󠆅󠆞󠄒󠇃󠇬󠇁󠄎󠇗󠄬󠆆󠅱Reality: The New York Times never published this figure. 󠇟󠇠󠇡󠇢󠄕󠄠󠆤󠄮󠆜󠄞󠄱󠄺󠅺󠅄󠅥󠆪󠆺󠄻󠄐󠅛󠄡󠄻󠆐󠄶󠇯󠅼︋󠆏󠅛󠅮󠄤󠇥󠇥󠄰󠅭󠅩󠅥󠆗󠄉󠇘󠄃󠄞󠄁󠇌The AI invented it. *

󠇟󠇠󠇡󠇢󠆸󠄾󠅀󠅸󠇌󠅞󠄸󠅬󠆩󠅈︂󠅁󠆥󠅔󠇄󠅱󠅲󠅕󠄊󠅄󠄀󠆼󠅧󠅼󠆡󠇬󠆯󠄺󠇤󠄓󠄅󠆥󠇌󠇨󠆀󠇨󠄁󠅽󠇥󠅺### Modified Quotes

The AI reproduces something close to a real quote but changes key details—numbers, names, dates, or qualifiers. 󠇟󠇠󠇡󠇢󠄑󠇤󠄛󠇯󠄕󠅘󠄰󠄌󠅿󠅡󠅟󠅓󠅕󠄾󠅋󠄍󠆦󠆑︃󠇞󠄾󠆲󠇁󠆦󠅨󠄴󠄜󠄒󠄬󠇣󠆁󠅆󠄁󠄩󠅕󠅐󠇘󠅓󠆟󠆝Example:

"󠇟󠇠󠇡󠇢󠅡󠇇󠆛️󠄻󠅟󠄳󠇪󠆡󠆩󠅆󠆰︌󠇩󠆗󠅳󠇗󠇘󠄑󠄵󠅻󠄝󠇃󠆇󠅰󠆈󠄐󠇧󠇌󠆞󠇄󠇔󠆠󠅞󠇥󠇡󠆞󠇄󠆮󠆺Reuters reported that the study found a 'significant increase' in cases." *󠇟󠇠󠇡󠇢󠅵󠄻󠄛󠅫󠇀󠇚󠄴󠇗󠆂󠄕󠄞󠇃󠇟󠇁󠄖󠅪󠄰󠇗󠄫󠅔󠅲󠄽󠇧󠄫󠄇󠆎︈󠅮󠆺󠇚󠄋󠅗︈󠄙󠅣󠆦󠅭󠅢󠄘󠆤Reality: Reuters reported a 'modest increase'—a meaningful difference. *

󠇟󠇠󠇡󠇢󠆵󠄃󠅲󠄱󠆦󠆑󠄿󠄜󠆓󠆬󠇏󠇟󠅤󠅖󠄓󠅠󠆱︇󠇂󠅪󠄌󠆽󠆎󠆨󠅒󠅩󠇓󠄅󠄜󠄀󠅜󠆲󠄣󠅎󠄜󠄇󠄡󠆒󠆹󠇕### Misattributed Quotes

The AI attributes a real statement to the wrong source. 󠇟󠇠󠇡󠇢󠄗󠇣󠆷󠆮󠆪󠅸󠄵󠇠󠆏󠄭󠄳󠅬󠅨󠄡󠄸󠅉︊󠇄󠇋󠅿󠅼󠅬󠇂󠇀︉󠄊󠇁󠆽󠆋󠄲󠆔󠄒󠆄︃󠅿󠇅󠅼󠄚󠅂󠇮Example:

"󠇟󠇠󠇡󠇢󠇢󠇞󠆈󠅭󠄸󠆱󠄺󠅓󠆑󠄞󠇪󠄋󠄦󠆿󠅽󠅽󠅢󠆝󠆙󠇈󠅴󠆎󠅢󠇜︍󠅻󠄵󠄩󠅳󠅎󠅹󠇍󠇘󠄨󠄩󠅪󠄝󠄽󠆾󠆚As the BBC reported, the policy will take effect in January. "

*󠇟󠇠󠇡󠇢󠆥󠄶󠇀󠅞󠅉󠆅󠄺󠆽󠆭󠅞󠅢󠇕󠅅󠄳󠄷󠅟󠇒󠇂󠄘󠄸󠅾󠅗󠅾󠄌󠅨󠇏󠅘󠆞󠄱󠅥󠅊󠄆󠅾󠇩󠄃󠆛󠅠󠆜󠄿󠄂Reality: CNN reported this, not the BBC. *

󠇟󠇠󠇡󠇢󠇙󠆀󠄵󠇄󠆑󠄰󠄶󠄜󠆝󠆀󠆋󠅱󠆗󠆱󠅕󠅭󠅻󠅻︊󠆮󠅸󠄳󠇌󠇌󠇐󠅡󠆇󠄼󠆗󠆒󠆮󠄻󠄕󠅼󠄈︌󠄞󠄛󠅇󠄀### Context Stripping

The AI reproduces a quote accurately but removes crucial context that changes its meaning. 󠇟󠇠󠇡󠇢󠄙󠇕󠇑󠅘󠅷󠇂󠄴󠇀󠅲󠄕󠇇󠆝󠇕󠆄󠆥󠆻󠆴󠇎󠅆󠆷󠆋󠅜󠅨󠄝︇󠆩󠄼󠆯󠅥󠇄󠆓󠇭󠇝󠅮󠆻󠄇󠄡󠇓󠇭󠆝Example:

"󠇟󠇠󠇡󠇢󠆚󠆥󠆌󠆠󠄌󠅟󠄲󠆕󠅱󠇜󠄂󠇛󠆡󠆚󠄎︆󠆻󠆘󠇭󠄭󠅙󠄀󠆦󠄊󠆨󠆕󠄪󠇆󠆔󠇉󠄤󠄚󠆋󠇒󠆋󠄸󠆹󠆰󠆂󠇕The Washington Post noted that 'crime rates have risen dramatically.' "

󠇟󠇠󠇡󠇢󠄲󠆒󠄌󠆞󠆭󠄆󠄹󠇫󠅱󠆖󠆼󠇑󠆌󠆾󠅬󠆕󠆐󠅝󠄕󠇪󠄐󠄙󠄭󠆷󠆓󠆃󠇩󠅊󠆄󠇈󠄝󠆫󠅡󠅬󠅵󠅩󠄉󠅉󠅾󠅍Reality: The full quote was "While some claim crime rates have risen dramatically, the data shows a more nuanced picture. "

󠇟󠇠󠇡󠇢󠅪󠄀󠆬󠄿󠅃󠇝󠄰󠅹󠅷󠅱︅󠆈︊󠆰󠅝󠅅󠄗󠆸󠇭󠆀󠄎︀󠇂󠄥󠅩󠆣󠅛󠆅󠆩󠄆󠆵󠆰󠄅󠇍󠅯󠄮󠅝︅︈󠅻## Why This Matters for Publishers

When AI systems misattribute or fabricate quotes, the damage falls on the cited publisher:

Reputation Damage

Your brand becomes associated with information you never published. 󠇟󠇠󠇡󠇢󠄧󠇉󠆈󠅝󠇎󠄌󠄸󠆟󠆧󠇨󠆧󠆠󠄭󠄿󠄬󠇈󠅯󠇭󠇧󠇆󠄣︅󠆌󠇐󠅋󠆫󠅖󠄄󠆺󠆛󠄷󠆰󠆕󠆭󠆘󠄗󠆀󠇦󠅽︁Readers who trust the AI's attribution may lose trust in your publication when they discover the discrepancy.

Credibility Erosion

Each false attribution chips away at the credibility you've built over years or decades. 󠇟󠇠󠇡󠇢󠅷󠄁󠇚󠆰󠄧󠄳󠄱󠇒󠆀󠄂󠆬󠄔󠄂󠄚︇󠄇󠅧󠇄󠅃󠆨󠇁󠆓󠄰󠄞󠅯󠅰󠅼󠅞︊󠅎󠆇󠄸󠄁󠆒󠄿󠄔󠇫󠇖󠇑󠆯In an era of declining trust in media, you can't afford AI-generated erosion.

Legal Exposure

If a fabricated quote attributed to your publication causes harm—defamation, market manipulation, public panic—you may face legal questions even though you never published it.

Correction Burden

When false quotes circulate with your attribution, you face the impossible task of correcting information you never published in the first place. 󠇟󠇠󠇡󠇢󠅄󠇎󠆫󠄾󠇂󠆽󠄵󠄊󠅴󠇍󠄔󠄦󠇆󠆜󠇀󠇤󠇤󠄗󠇁󠇐󠅖󠆂󠇥󠄂󠅲󠄏󠅸󠄴󠇥󠇦󠇦󠇀󠅷󠆪︄󠄡󠇛󠇩󠅟󠇊## 󠇟󠇠󠇡󠇢󠆥󠆷󠆠󠄂󠇑󠄳󠄰󠅐󠆭󠆗󠇡󠅮󠇟󠄎󠄋󠆾󠄣󠅆󠅧󠄗󠇪󠆳󠆶󠇪󠅅󠄳󠇧󠄙󠅥󠆦󠆃󠇌󠅄󠇯󠄺󠇀󠄢󠅢󠆜󠄺The Scale of the Problem

AI hallucination isn't a rare edge case—it's endemic: ### Research Findings

Studies have found hallucination rates varying by task and model: | Context | Hallucination Rate | |---------|-------------------| | General knowledge questions | 15-25% | | Specific factual claims | 20-40% | | Citations and attributions | 30-50% | | Medical/legal information | 10-30% |

Real-World Examples

Legal Citations: 󠇟󠇠󠇡󠇢︌󠄳󠆋󠅚󠆥󠄕󠄽󠇚󠅿󠆸︀󠄂󠄶󠇁󠇜󠄗󠅯󠇢󠆨󠄳󠆄󠅞󠆐󠄛󠄤󠇦󠅣󠆂󠄇󠄉󠇨󠇌󠅍󠆜󠅉󠄊󠅜󠄊󠅕󠄟Lawyers have submitted briefs citing cases that don't exist, generated by AI systems that fabricated case names, citations, and holdings. 󠇟󠇠󠇡󠇢︄󠅼󠄈󠅇󠅂󠇯󠄺󠅣󠅴󠆛󠅏󠆇󠄘󠇆󠄂󠇪󠇍󠄃󠇞󠆝️󠅛󠇈󠇘󠆨󠇈󠄙󠄒󠄕󠆋󠅬󠄆󠅄󠅀󠄰󠇬︍󠄀󠄵󠄔Academic Citations: 󠇟󠇠󠇡󠇢󠇇󠅾󠇘󠆿󠆂󠆮󠄶󠅊󠅹󠆮󠄅󠅥󠅗󠅹󠅕󠄯󠇃󠄖󠅮󠄑󠆨󠆿󠆽󠇠󠅼󠆫󠆆󠆏󠆾󠅥︇󠄵󠄌󠅮󠅿󠅟󠇓󠇭󠇄󠆲Researchers have found AI-generated papers citing non-existent studies with plausible-sounding titles and authors. 󠇟󠇠󠇡󠇢󠄦󠅊󠇘󠆗󠆖󠄒󠄻󠇢󠆚󠇟󠆽󠆒󠆢󠆪󠄍󠄘󠅒󠅬󠄏󠇬󠆌󠅌󠅩󠅨󠄃󠇧󠄡󠇁󠆚󠅚󠇂󠅓󠄫󠇯󠆃󠇮󠄽󠅇󠆉󠅚News Attribution: 󠇟󠇠󠇡󠇢󠅡󠄃󠅾󠅙󠇆󠇤󠄳󠆴󠆜󠇌󠇋󠅚󠄒󠅩️󠇟󠇈󠄎󠄊󠅝󠆴󠇀󠅶󠇎󠄂󠅭︂󠇮󠅆󠆼󠆱󠄞󠄍󠄀󠅆󠅑󠆀󠆇󠇮󠅲Fact-checkers regularly encounter AI-generated content attributing false statements to legitimate news organizations. 󠇟󠇠󠇡󠇢󠆊󠅎󠆺󠅖󠇌󠄟󠄶󠇎󠆔󠅬󠄻󠅺󠅔󠆸󠆓󠆘󠆰󠅻󠆧︂󠆏󠇆󠅵︂󠄖󠅪󠄆󠅏󠆝󠅒󠆶󠇫󠄞󠄑󠇦󠆜󠄨󠄜󠄖︍## Why Traditional Solutions Fail ### Disclaimers Don't Work

AI systems can include disclaimers like "I may make mistakes," but users often ignore them—especially when the content looks authoritative with specific attributions. 󠇟󠇠󠇡󠇢󠄫󠆌︅󠆉󠇍󠆈󠄾󠆆󠆘󠆹󠅝󠅒󠇩󠇢󠄠󠅮󠄣󠄄󠄟󠅲󠇩󠆋󠆏󠇏󠅚󠅝󠄸󠄕󠅮󠅯󠄓󠆘︀󠅯󠇞󠄠󠄕󠅨󠄽󠅤### Fact-Checking Doesn't Scale

Manual fact-checking can't keep pace with AI-generated content. 󠇟󠇠󠇡󠇢󠇎󠅧󠄊󠅬︂󠄟󠄵󠅌󠆧󠄐󠅴󠄐󠇩󠅸󠅉󠆐󠄛󠄒󠇝󠄼󠄉󠆑󠄛󠅹󠄍󠆾󠆑󠆪󠆃󠆸󠆖󠆛󠅾󠅍󠆛󠅽︂󠅗󠇎󠄒For every false attribution caught, thousands more circulate unchecked.

Detection Is Unreliable

AI detection tools can't identify hallucinated quotes. 󠇟󠇠󠇡󠇢󠅟󠅸󠆑󠄉󠅝󠅶󠄴󠅚󠆗󠅞󠅫󠄺󠄐󠅡󠆰󠆡󠅽󠆒󠆣󠄷󠅏󠆝󠄿󠄕󠄻󠄜󠅩󠆅󠆣󠄷󠇂󠅪󠇏󠄸󠆸󠆳󠆡󠄒󠅿󠅆They analyze writing style, not factual accuracy. 󠇟󠇠󠇡󠇢󠅏󠅎󠄃󠄇󠄍󠇜󠄺󠇆󠆎󠆧󠅷󠆃󠄨󠅵󠅿󠆴︌󠆽󠅅󠅺󠄏󠇪󠄦󠇎󠇓󠆩󠅕󠆂󠄳󠄮󠅿󠆾󠅈󠅅󠄫󠅝󠆾󠆀󠆢󠆆### Corrections Come Too Late

By the time a false attribution is identified and corrected, it may have spread widely and caused damage. 󠇟󠇠󠇡󠇢︋󠄹󠄴󠇙󠅄󠄟󠄱󠅭󠆔󠄌󠇭󠅄󠆷󠄡󠇦󠇬󠆷󠄢󠄃󠇋󠆶󠇓󠅱︎󠇜󠇉󠄂󠅓󠇓󠆢󠆔󠆫󠅛󠄴󠄃󠆝󠅝󠇚󠇂󠄌## 󠇟󠇠󠇡󠇢󠅜󠄐󠆋󠆐󠅡󠇀󠄱󠆃󠆏︇󠇏󠄇󠆇󠅦︄󠅁󠅤󠇎󠇍󠅴󠅧󠄑󠄬󠅳󠄍󠇋󠄫󠆭󠇎󠅩󠆉󠄅󠆹󠄞󠅈︂󠆋󠅲󠄢︇The Quote Integrity Solution

Quote integrity verification takes a fundamentally different approach: instead of trying to detect hallucinations after the fact, it enables verification at the moment of use.

How It Works

  1. 󠇟󠇠󠇡󠇢󠄉󠇒󠇆󠇌󠇁󠄿󠄶󠇌󠅹󠄶󠅳󠄏󠄱󠅇󠅪󠆆󠄐︊󠄣󠇯󠄃󠅦󠆝󠅐󠅙󠅹󠅠󠄯︉󠇝󠅜󠄪󠄊󠄲󠆍󠄜󠄕󠅊󠅉󠆰Publisher signs content with cryptographic provenance at publication
  2. 󠇟󠇠󠇡󠇢󠄾󠇮󠅕󠅵󠅰󠄶󠄲󠆴󠅷️󠇥󠇩󠇒󠄢󠅚󠆂󠅿󠆣󠇪󠆷󠆞󠅔󠅨󠇑󠇔󠄋󠅸︁󠇤󠇈󠅷󠆳󠆖󠆓󠆊󠅓󠅹󠅥󠆥󠄵Signatures are embedded at sentence or paragraph level
  3. 󠇟󠇠󠇡󠇢󠇍󠄐󠅑󠅺︃󠄇󠄽󠄂󠅼󠄁󠅟󠅥󠅄󠅁󠆺󠅆󠅉󠄖󠅷󠄨󠄆󠄣󠅿󠆷󠆰󠅱󠅚󠇖󠄜󠆦󠆌󠆀󠅂󠆠󠄱󠇩󠅲󠇀󠆻󠅦AI system (or user) queries the verification API with a claimed quote
  4. 󠇟󠇠󠇡󠇢󠆹󠅗󠆕︌︋󠇉󠄾󠅭󠆨󠅬󠆯󠄆󠇄󠆳󠇫󠇝󠇞󠇧󠇠󠆎󠆼󠇄󠄲󠅢󠅞󠆇󠆽󠄸󠇣󠅌󠆷󠄜󠄂󠇙󠄨󠆛󠄼︋󠅌󠆎System returns verification status:
    • ✅ Verified — Quote matches signed content exactly
    • ⚠ Modified — Similar content exists but has been altered
    • ❌ Not Found 󠇟󠇠󠇡󠇢󠄂󠅧󠅩︈󠄰󠇤󠄿󠄨󠆬󠅞󠅂󠅈󠆞︁󠆟󠇢󠆣󠄲󠄐󠆓󠅍󠅄󠄁󠅺󠅚󠅍󠅆󠄮󠄝󠆔󠅑󠆨󠅳󠄯󠅶󠅲󠇇󠆍󠇃󠄣— No matching signed content exists

󠇟󠇠󠇡󠇢󠆕︉󠄻󠇒︎󠅈󠄴︃󠆇󠇓󠅵󠆴󠄭󠄱󠆕󠅛︀󠇀󠅘󠆭󠅁󠆳󠇒󠆪󠇒󠆱󠄼󠄼󠄋󠆨󠇆󠇓󠄿󠆒󠇥󠇪󠄧󠇟󠅜󠆯The Verification Flow

User/AI: "According to AP, the unemployment rate fell to 3.7%"
         ↓
Verification API: Check against AP's signed content
         ↓
Response: ✅ Verified — Matches article published 2025-10-15
         OR
Response: ⚠ 󠇟󠇠󠇡󠇢󠅻󠅄󠅈󠇘󠄅󠆆󠄿󠅾󠅽󠇮󠆄󠄦󠆂󠆕󠄲󠇔󠆏󠆟󠅒︁󠇀󠅓󠅃󠄶󠆮󠆧󠄀󠄋󠄠󠆰󠆑󠆎󠅋󠄈󠅀󠇉󠄁󠄥󠄙󠆂Modified — Original said 3.9%, not 3.7%
         OR
Response: ❌ Not Found — AP has no signed content matching this claim

󠇟󠇠󠇡󠇢󠇘󠆒󠄡󠄂󠄁󠇛󠄰󠇦󠆉󠅗󠄘󠄟󠆟󠇎󠇆󠇘󠄓󠄁󠄘󠅟︁󠄼󠆳󠄨󠅯󠄣󠆕󠆙󠇥󠅯󠅝󠅥󠆈󠄙󠄝󠆰󠇐󠆀󠇗󠄹What This Enables

For Publishers:

  • Protect brand from false attribution
  • Provide verification service to AI companies
  • Create new value from content provenance

For AI Companies:

  • Verify attributions before output
  • Reduce hallucination liability
  • Build trust with users

For Users:

  • Check AI-generated attributions
  • Distinguish verified from unverified claims
  • Make informed decisions about trust

󠇟󠇠󠇡󠇢󠆫󠆻󠄨󠆨︍︆󠄾󠆈󠅿󠄛︊󠄠󠅛︌󠄙󠅖󠇉󠇧󠆻󠄰󠄃󠄻󠆸󠄥󠆁󠄟󠄃󠅲󠅉󠇉󠄃︇󠆀󠅫︁󠄊󠄬󠆠󠅒󠄮Implementation Approaches

Publisher-Side Implementation

Publishers implement quote integrity by:

  1. 󠇟󠇠󠇡󠇢󠅽󠅭︈󠅋󠆓󠆚󠄱󠆶󠅼󠄟󠄅󠅃󠆅󠆇󠄣󠆽󠅷󠄎︂󠅡󠆐󠇭󠄇󠆳󠄤󠄅󠇣󠅐󠆦︄󠄟󠅰󠇂󠄣󠄇󠆔󠇍󠅸󠅖󠆉Signing content at publication — 󠇟󠇠󠇡󠇢󠅼󠆒󠄥󠄢󠇞󠅝󠄵󠅎󠆄󠅯󠄸󠅻󠄴️󠇆󠇔󠆮󠆄󠅠󠆓󠄳󠄕󠇎󠅜󠄪󠄭󠅟󠇧󠅳󠄌󠇙󠅆󠅸󠅰󠆬󠄤󠄭󠆉󠅎︈Every article gets cryptographic provenance
  2. 󠇟󠇠󠇡󠇢󠆉󠇕󠆀󠅊󠅁󠇐󠄰󠄭󠆡󠄯󠅷󠆊󠆢󠅯󠇒󠅿󠇓󠇬󠆶󠆎󠇖󠇒󠅪󠆐󠆓︇󠅤︇󠆏󠆔󠆣󠅈󠆎󠄀󠇓󠅀󠇊󠅶󠆛󠄍Maintaining verification API — Endpoint for quote verification queries
    • 󠇟󠇠󠇡󠇢󠅢󠄡󠄬󠅪󠆨󠇜󠄳︅󠅵󠄃󠅁󠆶󠄧󠇘󠇧󠄞󠅸󠇂󠅵󠄼󠅬󠅰󠄱󠄻󠄸󠄥󠅍󠅶󠄢󠇍󠅮󠄙󠆹󠅻󠅝󠄷󠆄󠅍󠄤󠇮Indexing for search* — Efficient lookup of signed content
    • 󠇟󠇠󠇡󠇢󠆄󠆿󠅊󠅷󠆼󠆵󠄼󠇧󠆡︇󠆅󠅴󠄤󠅞󠆪󠅆󠇟󠇮󠆷󠅬󠅤󠅞󠄖󠆝󠅽󠄩󠇓󠄉︎󠄝󠇣󠆟󠆁󠄏󠄝󠆦󠇂󠇂󠅪󠄰Providing access* — API access for AI companies and verification tools

AI-Side Implementation

AI companies can integrate quote integrity by:

  1. 󠇟󠇠󠇡󠇢︆󠅖󠇋󠅦󠇠󠅴󠄶󠆂󠆞︍󠆳󠆄󠆸󠅠󠅆󠄒󠄁󠅉󠆂󠆎󠇊󠅪󠅞󠆨︄󠅕󠆦󠆤︁󠅡󠅊󠆆󠄩󠅆󠄇󠅄󠆚󠆍︊󠆙Pre-output verification — Check attributions before displaying to users
  2. 󠇟󠇠󠇡󠇢󠇨󠆱󠅖︅󠄟󠆿󠄼︅󠆩︃󠆵󠇎󠄘󠇬󠅖󠅵󠆠︅󠄸󠇚󠆺󠅕󠇉󠄔󠆿󠅇󠇬󠆭󠅜︅︂󠆣󠅐󠆘󠅛︂󠄚󠄖󠅟󠇓Confidence indicators — Show users which quotes are verified
  3. 󠇟󠇠󠇡󠇢󠅜󠄤󠄘󠅣󠇫󠆘󠄰󠅢󠆨󠄞󠅂󠅹󠅠󠅛󠆋󠄁󠆪󠆝󠆰󠆿󠄤󠄧󠆀󠅨󠇡︅󠅥󠄞󠄈󠆷󠄿󠄟󠅈󠇦󠄷󠄂󠅽󠆟󠅇󠇃Fallback handling — Flag unverifiable attributions appropriately
  4. 󠇟󠇠󠇡󠇢︉󠇠󠅮󠅂󠅀󠆳󠄳󠇢󠆚󠄚󠆐󠄙󠅏󠅦󠇙󠅈󠄣︍󠇓󠄭󠄻󠄷󠇬󠅀󠅷󠆨󠆥󠇢󠇁︁󠅄󠄄︎󠆥󠄶󠇇︅󠆸󠆒󠅻Feedback loops — Use verification results to improve accuracy

User-Side Implementation

End users can verify quotes through:

  1. 󠇟󠇠󠇡󠇢󠆊󠇚󠆳️󠅆󠆃󠄼󠇘󠆄󠇂󠇟󠅩󠄝󠆝󠆫︍󠇢󠆥󠄼︅󠄢󠇌󠄇󠄜󠅨󠄷󠆊󠇞󠅁󠅣︋󠇁󠄙󠄱󠇅󠄞󠅏󠇑󠅒󠄌Browser extensions — Automatic verification of attributed quotes
  2. 󠇟󠇠󠇡󠇢󠄢󠆓󠇇󠄞󠇚󠆌󠄵󠆕󠆢󠆴󠄳󠆕︈󠅘︅󠅿󠇙󠄁󠄓󠄏󠆾󠆖󠇚󠅬󠆐󠆔󠇒󠇟󠆥󠆯󠇭󠅪󠇒󠅌󠅟󠄹󠅒󠄍󠆍󠄰Verification websites — Paste a quote to check its authenticity
  3. API access — For developers building verification into applications

󠇟󠇠󠇡󠇢󠇦󠅘󠇇󠅹󠄌󠅑󠄻󠆂󠆎󠄑󠄝󠄘󠆾󠄈󠄢󠄭󠅶󠆢󠆐󠅘󠇋󠅱󠆃󠇩︋︎󠆚󠄊󠆟󠅈︊󠇣󠅠󠇬󠄇󠆮󠅄󠅎󠅊︅The Business Case

Quote integrity verification creates value for multiple stakeholders:

For Publishers

Brand Protection: 󠇟󠇠󠇡󠇢󠇡󠇚󠅆󠇒󠆶󠄯󠄹󠅱󠆑󠆎󠇠󠆹󠅱󠆠󠆍󠄤󠇞󠄈󠆨󠅶󠆄󠇄󠇣󠄊󠆓󠄦󠇢︆󠆴󠄔󠄥󠆌󠄪󠄁󠆫󠅓󠇩󠅢󠇕󠇄Prevent reputation damage from false attribution

New Revenue Stream: License verification API access to AI companies

Competitive Advantage: 󠇟󠇠󠇡󠇢󠇯︋󠆕󠄫︍󠇢󠄿󠇑󠅽󠇑󠇡󠇕󠄸󠇤󠅣󠇔󠆬󠆜󠅭󠅣󠅢󠄎󠅒󠆫󠆐󠆼󠅱󠄌󠇒󠅿󠄌󠆠󠆅︅󠇇󠅘󠅚󠇧󠇉󠆈Verified content is more valuable than unverified

*Licensing Leverage : * 󠇟󠇠󠇡󠇢󠆼󠇅󠆙󠅢󠆿󠅻󠄵󠆯󠆩󠄈󠆉󠄶︅󠄿󠆮󠇣󠆾󠇋󠅜󠅵󠄫󠄺󠆻󠆨󠇓󠄥󠄎󠇃󠆌󠅎󠄧󠄕󠄡󠄊󠄄󠅇󠅖󠆋󠅎󠇫󠇟󠇠󠇡󠇢󠅗󠆂󠄱󠆵󠆼󠇓󠄷󠆑󠆌󠆝󠄀󠆴󠄱󠆄󠇣󠆒︃󠆚󠄱󠄺󠆦󠅴󠄼󠇠︈󠅗󠄌󠅅󠆋󠇂󠄟󠄁󠇏󠅛󠅦󠆫︎󠄺󠄐󠆩Quote integrity is a feature AI companies will pay for

For AI Companies

Reduced Liability: 󠇟󠇠󠇡󠇢󠄯󠄗󠇂󠇪󠅰󠇠󠄾󠅶󠅲󠆨󠄗󠇖󠆓󠇑󠆫󠄢󠅅󠅃󠄞󠇁󠄓󠆒󠇛󠆄󠄲︊󠅘󠆃󠆨󠆣󠆗󠅎󠇢󠇡󠇚󠅥󠆥󠄌󠄕󠇞Verified quotes reduce hallucination-related legal exposure

User Trust: Verification indicators build confidence in AI outputs

Quality Differentiation: "󠇟󠇠󠇡󠇢󠆳󠆃󠅁󠇋󠆞󠆱󠄰󠆂󠆎󠅃󠄕󠄱󠄴󠇙󠆡󠅊󠄵󠆫󠄩󠅌󠄇󠆠󠄭󠆟󠆜󠅞󠆍󠇎󠅟󠇝󠅡︇󠆧󠅙󠅕󠄷󠄉󠄪󠅮󠇢Verified attributions" becomes a competitive feature

Publisher Relationships: 󠇟󠇠󠇡󠇢󠇤󠄴󠄷󠆚󠆘󠅁󠄿󠆮󠆚󠆥󠅖󠅡󠆦︉󠇍󠇔︈󠇁󠇉󠇈󠄔󠇐️󠆵󠅄󠆯󠆆󠅴󠇟󠇁︅󠅢󠆻󠆡󠅙󠄷󠅐󠄄󠅄󠆹Quote integrity enables licensing partnerships

For the Ecosystem

Trust Infrastructure: 󠇟󠇠󠇡󠇢󠆽󠇮󠇈󠅑󠅗󠆠󠄿󠆠󠅲󠄅󠅺󠅨󠅼󠄽󠇆󠇄󠇐󠇉󠆩󠄫󠄒󠅓󠄢󠆫󠆐󠇫󠆔󠅾󠄗󠇀󠅧󠄢󠅙󠇃󠅣󠇒󠇞󠄩󠆃󠇋Verification creates a foundation for trustworthy AI

Standards Alignment: Fits with C2PA and content authenticity initiatives

Regulatory Compliance: Supports transparency requirements

Challenges and Limitations

Coverage

Quote integrity only works for content that has been signed. 󠇟󠇠󠇡󠇢︆󠄠️󠅋󠅜󠄒󠄵󠅳󠆅󠄄󠄟󠄅󠆋󠆞󠇭󠇮󠅁󠅰󠅮󠅳󠅬󠆭󠅉󠅲󠆀󠅛󠄞󠆨󠇁󠆡󠅵󠆨󠇈󠅁󠅁󠅊︌󠆂󠆛󠇆Historical content without provenance can't be verified through this system. 󠇟󠇠󠇡󠇢󠅱󠄨󠄔󠇢󠄧󠆌󠄾󠇉󠅽󠆫󠅇󠅃󠅁󠅧︃󠆿󠅫󠆨󠅧󠆰󠅛󠇯󠅻󠆧󠄵󠅠︄󠅺󠄘󠅉󠄀󠆿󠆨󠇝󠇇󠆗󠅝󠄩󠄠︃Mitigation: 󠇟󠇠󠇡󠇢󠄐󠇢󠆬󠆱󠄒󠆩󠄿󠇡󠆜󠆚󠆄󠆂󠇖󠇯󠇨󠄸󠆂󠅽󠅟󠄺󠄹󠆍󠅜󠄕󠇓󠅆󠅏󠅎󠇨󠇤󠄻󠅰󠅒󠄏󠄺󠅶󠇣󠄓󠆂︄Publishers can retroactively sign archived content, though this requires effort and doesn't provide the same timestamp guarantees.

Paraphrasing

Exact quote matching may miss legitimate paraphrasing that preserves meaning. 󠇟󠇠󠇡󠇢󠄷󠇌󠄸󠆅󠆧󠆁󠄱󠇮󠆍︊󠅑󠄆󠆜󠅳󠆜󠆌󠅉︋󠇤󠅔󠇨️󠇔󠄨󠅜󠄪󠄀󠇍󠅹󠄅󠆱󠄭󠇗󠇉󠄇󠅐󠇙󠇙󠄭󠄶Mitigation: 󠇟󠇠󠇡󠇢󠅒󠄰󠅌󠆠󠆰󠅫󠄸︈󠆝󠇇󠇠󠅆󠄍󠇥󠇓󠆵󠆭󠆇󠄉󠅨󠅍󠅘󠆨󠆻󠄘󠄌󠇡󠆅󠄠󠆘󠅍󠆞󠆺󠅤︋󠆠󠇉󠅑󠄛󠅷Semantic similarity matching can identify paraphrases, though with less certainty than exact matches.

Adoption

The system requires both publishers and AI companies to participate. 󠇟󠇠󠇡󠇢󠅚󠅽󠄡󠇄󠇙󠇞󠄺󠄥󠆈󠄥󠅳󠅧󠆨󠄴󠅂󠄔󠄁󠆜󠅶󠇑󠄈󠅈󠅜󠆎󠆬󠅂󠄶󠇇󠅩︌󠅫󠅌󠇐󠅶󠆘󠇙󠇭󠅨󠇉󠆇Mitigation: 󠇟󠇠󠇡󠇢︊󠄴󠄰󠄹󠅈󠆟󠄽󠄧󠅱󠆁󠅊󠅸󠆢󠆗󠆬󠆑󠄰󠆿󠅝󠅀󠇇󠇗󠅓︌󠄩󠇦︊󠄲󠇣󠄄󠅶󠄰󠄔󠅭󠄢︇󠄝󠅯󠅐󠄅Network effects—as more publishers sign content, AI companies have more incentive to verify; as more AI companies verify, publishers have more incentive to sign. 󠇟󠇠󠇡󠇢︂︊󠅹󠆉󠆔󠅵󠄷󠆍󠆎󠆓󠆆󠄀󠄦󠅉󠄬󠄺󠅃󠆒󠆚󠆠󠆧󠅍󠄃󠅋󠅀󠆓󠇬󠄆󠆈󠅮󠆣󠅩︃󠄑󠄈󠄉󠇍󠄒󠅱󠅐### Performance

Real-time verification adds latency to AI responses. 󠇟󠇠󠇡󠇢󠆕󠆞󠅇󠄁󠇦󠇡󠄶󠅤󠆌󠆍󠄵󠅱󠅕󠅲󠇭󠆻󠆝󠄍󠅿󠇛󠄎󠆍󠆏󠅟︁󠇍︍󠇚󠅨󠇀󠇭󠅥󠆼󠄤󠇯󠅬󠅆󠄍󠆾󠄞Mitigation: Caching, pre-computation, and efficient indexing can minimize performance impact. 󠇟󠇠󠇡󠇢󠆚󠆝󠅍󠇮󠄥󠅅󠄳󠆇󠆯󠆯󠇝󠇜󠅡︍󠇂󠄎󠄻󠅘󠆺󠄟󠅲󠅒󠇋󠄘󠆽󠅊󠄕󠆙󠆲󠄕󠄴󠆪󠆫󠆧󠆀󠄓󠄉󠇠󠄝︍## 󠇟󠇠󠇡󠇢󠅲󠆍󠆯󠆻󠆿󠄩󠄻󠅖󠆠󠅍󠆼󠅩󠄂󠇧︂󠄈󠅎󠆊󠄜️󠇫󠄺󠅘󠆢󠆯󠄀󠆌󠇌︁󠇞󠆐󠇪󠅦󠆝󠇆󠆮󠆪󠄶󠇈󠅆The Path Forward

Quote integrity verification is becoming essential infrastructure for the AI era:

Near-Term (2025-2026)

  • Major publishers implement content signing
  • AI companies begin integrating verification
  • Standards emerge for quote verification APIs
  • Early adopters gain competitive advantage

Medium-Term (2026-2027)

  • Verification becomes expected for attributed content
  • Unverified attributions carry implicit uncertainty
  • Licensing deals include quote integrity provisions
  • Regulatory frameworks reference verification standards

Long-Term (2027+)

  • Quote integrity is table stakes for credible AI
  • Verification infrastructure is ubiquitous
  • False attribution becomes legally and reputationally costly
  • Trust in AI-generated content is rebuilt on verification

󠇟󠇠󠇡󠇢󠅘󠄮󠆣󠄐󠆾󠅂󠄳󠄨󠆭󠇖︋󠅍󠇮󠇚󠄐︋󠇎󠆲︆󠅂󠅇󠆘󠆇󠆮󠇢󠅐󠆜󠅮󠆅󠄆󠅁󠇜󠄿︇󠆇󠇘󠅕󠅿󠆊󠆧What Publishers Should Do Now

Immediate Actions

  1. 󠇟󠇠󠇡󠇢󠇊󠅑󠅗󠆱󠄸󠆻󠄷󠄏󠆫󠄹󠆆󠆇󠄙󠆨󠅑󠄅󠆩󠄓󠄊󠆤󠆚󠇧︉󠅐󠅏︍󠇙󠆭󠆏󠅊󠅝󠆧󠅹󠇌󠆐󠄿󠆹󠇢󠄇󠅏Assess exposure — How often is your publication cited by AI systems? 󠇟󠇠󠇡󠇢󠄸󠆈󠇗󠄈󠆔󠇈󠄸󠆢󠅶󠅶󠄥󠆍󠄺󠄶󠄤︆󠇚󠆫︍󠆪󠇞󠅕︌󠄥󠆥󠆧󠅱󠅜󠅡󠄁󠄹󠄡󠄐󠅙󠇑︉󠅕󠇑󠆼󠅥2. 󠇟󠇠󠇡󠇢󠅨󠆼󠆮󠅺󠄶󠇍󠄴󠇍󠆒󠅯󠅿󠅝󠅂︌︊󠄛󠄠󠄾󠇂󠆰󠄂󠄝︎󠇃󠄠󠅳󠄎︀󠇥󠅢󠄷󠆘󠆋󠄓󠆏󠆓󠅾󠆄󠄷󠅀Document instances — Track false attributions when you find them
  2. Evaluate solutions — Understand quote integrity verification options

Implementation Steps

  1. 󠇟󠇠󠇡󠇢󠆎󠆗󠄍󠆗󠆷󠅋󠄺󠇯󠅱󠇋󠄸︉󠆅󠅷󠅃󠅻󠇥󠄿󠄔󠅅󠄩󠅾󠆯󠄧︉󠅡󠅒󠅔󠇟󠄉󠆉󠅾︌󠇨󠆰︀󠄈󠆴󠆂󠅚Implement content signing — Begin embedding provenance in new content
  2. 󠇟󠇠󠇡󠇢󠅮󠅱󠆴󠇎󠆿󠄣󠄻󠇤󠅵󠇭󠇦󠆼󠆜󠆆󠅑󠅀󠆌󠄅󠇝︁󠇕󠅗󠆇󠅎󠇅󠆰󠆧󠄷󠆧󠇃󠇖󠄃󠇣󠅷󠄁󠇬󠄕󠄌󠅈󠄽Build verification infrastructure — Create API for quote verification
  3. 󠇟󠇠󠇡󠇢󠄋󠆈󠇊󠆣󠅘󠆂󠄿󠇎󠅳󠆉󠅓󠇙󠅪󠅳󠄉󠅭󠄎󠆱󠅫󠆬󠆬󠅊󠆛󠇨󠄐󠄢󠄵󠇢󠄾󠆂󠄳󠄮󠆘󠅉󠅶󠅞󠅡󠅷󠅬󠆦Engage AI companies — Discuss verification integration and licensing
  4. 󠇟󠇠󠇡󠇢︁󠆰󠇤󠆈󠇧󠆗󠄾󠄚󠅾󠅱󠄣󠅫󠆾󠆎󠅿󠄭󠆒󠆻󠇀󠆈󠆺󠅻󠅣︄󠇩󠅉󠆓󠇛󠇛󠇪󠄽󠇉󠄃󠆳󠇃󠅙󠇛󠄅󠇀︂Communicate to audience — Explain your commitment to verified attribution

Strategic Positioning

  1. 󠇟󠇠󠇡󠇢󠅚︈󠄬󠇏󠄜󠄏󠄹󠄉󠆚󠄀󠇧󠆆󠆮︌󠇪󠅺󠇭󠆒︉󠆎󠄼︄󠇗󠅗󠄷󠇊󠆶︃󠅗󠅧󠄒󠆐󠄥󠅝󠅈󠄚󠇏󠄾󠄞󠆔Lead on standards — Participate in industry efforts to define verification protocols
  2. 󠇟󠇠󠇡󠇢󠅹󠄴󠄡󠅛󠇚󠅳󠄼󠄚󠆥󠇬󠄚󠄝󠅮󠇓󠄀󠆜󠅰󠆳︉󠄑󠄠󠄷󠇕󠆯︀󠆿󠅅󠇧󠄊󠅚󠄪󠆳󠆤󠄅󠄯󠇔󠆫󠅗󠇥︆Build partnerships — Work with AI companies on verification integration
  3. Create value — Position verified attribution as a premium feature

Conclusion

AI hallucination isn't going away. 󠇟󠇠󠇡󠇢󠅁󠆜󠆠󠆓︋󠄘󠄺󠄹󠅳󠆤󠆅󠆓󠆊󠆛︆󠅁︍󠆯󠆜󠆫󠇁󠅤󠄡󠅂󠆸󠇏󠆌󠇙󠆴󠆹󠅂󠄟󠅁󠅰󠅼󠅆󠅟󠄻󠆸󠄯Language models will continue to generate plausible-sounding but inaccurate attributions. 󠇟󠇠󠇡󠇢󠅑󠆤󠄢󠅔󠅯󠄮󠄼󠄏󠆧󠇈︍󠄾󠅩󠄽󠆱󠇍󠅸󠇊󠇣󠇦󠆎󠅎󠅛︌󠄭󠆫󠄜󠆈󠅾󠆔󠇒󠅥󠆘󠆪󠇧󠅘󠅑󠄸󠅅󠄋The question is whether publishers will be passive victims of this phenomenon or active participants in solving it. 󠇟󠇠󠇡󠇢󠇈󠅆󠆞󠅉󠇏󠄾󠄽󠇙󠅻󠆁󠇣󠆊󠅩󠅐󠇎󠄵󠅡󠄫󠄨󠅆󠄎󠅒󠅊󠄻󠇥󠄅󠅴󠇤󠅉󠆼󠅨󠆁󠅞󠇜󠆞󠆝󠆦󠅍󠄞󠅌Quote integrity verification offers a path forward: cryptographic proof that enables real-time verification of attributed quotes. 󠇟󠇠󠇡󠇢󠆚󠆉︈󠅰󠅩󠅀󠄴󠆦󠆥󠄿️󠅰󠄐󠅱󠆶󠇩󠆟󠅋󠄏︂󠄉󠆢󠅽󠆼󠅓󠅴󠆊󠅙󠄾󠅗󠆍󠆢󠄷󠇭󠅓󠇢󠄰󠄤󠆑󠅔Publishers who implement it protect their brands, create new value, and help build the trust infrastructure the AI era requires. 󠇟󠇠󠇡󠇢󠇏󠇇󠆮󠆳︎󠅒󠄱󠄝󠆈󠆸󠆯󠅾󠆆󠄍󠅳󠆔󠇎󠄔󠅥󠄌󠄽󠅿󠅒󠇆󠄂󠅶󠄛󠆚󠇯󠆦󠅲󠇊󠅄󠇃󠆚󠇊󠅪󠇢󠇀󠇦The alternative—watching your publication's name attached to statements you never made—is increasingly untenable. 󠇟󠇠󠇡󠇢󠇓︀󠅂󠄻󠇌󠆤󠄶󠄤󠆇󠆿󠄟󠆄󠅐󠄡󠆦󠇝󠅄󠄋󠇗󠄂󠄞󠄅󠄟︍󠄼󠅷󠄍󠆘󠆚︁󠄠󠄻󠆛󠆙󠄢󠅑󠅡󠆁󠆕󠄀Learn more about quote integrity verification: 󠇟󠇠󠇡󠇢󠅧󠇆󠅔︂󠇆󠄷󠄵󠅝󠆫󠄶︁󠅀󠄸󠅂󠅙󠅲󠇯󠇒󠇫󠆧󠆳󠇗︀󠆠󠆐󠅈󠅱󠅞󠅇󠅦󠅒︅󠄝󠆩󠄧󠅣󠅴󠅇󠆴󠅠encypherai.com/publisher-demo

#AIHallucination #QuoteVerification #BrandProtection #ContentAuthenticity #Trust󠇟󠇠󠇡󠇢󠇒󠄪󠇡󠆖󠆧󠇀󠄾󠄢󠆄󠇮󠇏󠆟󠆮󠆰︈󠇏󠄬󠆭󠆐󠄈󠆹󠇤󠅉󠅔󠆕󠅘󠆄󠄛󠇌󠅾󠇖󠇧󠅔󠆹󠅛󠇝󠅳󠇐󠄚󠄽

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#AIHallucination#QuoteVerification#BrandProtection#ContentAuthenticity#Trust
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