How ShouldEye Works

70+ AI models • Independent sources

One Question. Multiple Models. More Evidence.

ShouldEye combines web intelligence, source analysis and multiple AI systems to help you research companies, people, websites, products, games, scams and more from multiple perspectives.

EyeQ organizes the available signals into clearer findings about trust, risk, reputation and important context.

Trust Score

1–10

Trust Grade

A–F

  1. 01

    Web Sources

    Public information gathered from relevant online sources.

  2. 02

    EyeQ

    ShouldEye’s intelligence system organizes and compares signals.

  3. 03

    Multi-Model Analysis

    Multiple AI perspectives examine the same question.

  4. 04

    Signals

    Trust, risk, reputation and contextual indicators emerge.

  5. 05

    Findings

    Clearer intelligence for the subject being researched.

The Idea

Search Finds Information. ShouldEye Helps You Evaluate It.

Traditional search engines primarily help users find webpages. Individual AI systems can generate answers. Review platforms collect consumer experiences.

ShouldEye is designed to bring these types of intelligence together.

ShouldEye combines information from across the web, EyeQ analysis and multiple AI perspectives to help surface facts, trust signals, risks, disagreements and important context around the subject being researched.

  • Search

    Find information

  • AI

    Generate responses

  • Reviews

    Surface experiences

  • ShouldEye

    Evaluate the bigger picture

The Process

From Question to Intelligence

  1. 01

    Ask ShouldEye

    Research a company, person, website, product, game, scam, message, brand, service or another subject.

  2. 02

    Find Relevant Information

    ShouldEye identifies publicly available information relevant to the question.

    Depending on the subject, this may include:

    • official websites
    • company disclosures
    • policies
    • public records
    • legal information
    • regulatory information
    • news
    • consumer experiences
    • complaints
    • community discussions
    • security signals
    • other relevant online information
  3. 03

    EyeQ Analyzes the Signals

    EyeQ organizes and compares available information to identify:

    • useful facts
    • positive signals
    • potential risks
    • inconsistencies
    • supporting evidence
    • important context
  4. 04

    Multiple AI Perspectives

    ShouldEye can use multiple AI models and model-based systems to examine a question from different perspectives.

    The analysis depends on the mode selected.

  5. 05

    Get the Intelligence

    ShouldEye presents the findings in a structured response that can include:

    • trust signals
    • risk indicators
    • source information
    • evidence
    • model comparisons
    • EyeQ Trust Score
    • relevant context

EyeQ Intelligence

The Intelligence System Behind ShouldEye.

EyeQ is ShouldEye's AI intelligence system for analyzing trust, risk and information across the web.

EyeQ organizes and compares signals from relevant sources and AI systems to help users understand companies, people, websites, products, games, scams and other subjects.

EyeQ powers ShouldEye intelligence features including trust assessments, the EyeQ Trust Score and multi-model analysis.

Signals

Different Questions Require Different Evidence.

ShouldEye does not apply the exact same signals to every subject. EyeQ considers information based on what is being researched, which signals are relevant and what information is available.

  • Official Sources

    Company websites, disclosures and other official information.

  • Ownership & Transparency

    Available information about operators, organizations and ownership.

  • Terms & Policies

    Terms of service, privacy policies and other relevant policies.

  • Legal Information

    Relevant publicly available legal proceedings and records.

  • Regulatory Information

    Relevant government and regulatory information.

  • Consumer Experiences

    Reviews, complaints and publicly shared experiences.

  • News & Media

    Relevant published reporting and information.

  • Community Intelligence

    Relevant public discussions across communities and social platforms.

  • Reputation Signals

    Patterns that provide additional context about an entity's reputation.

  • Security Signals

    Available security information relevant to the subject.

The availability, relevance and quality of these signals vary by subject. ShouldEye does not assume every source carries equal weight.

EyeQ Trust Score

Complex Signals. One Clearer Assessment.

The EyeQ Trust Score is ShouldEye's proprietary trust and risk assessment for companies, websites, products, people, games and other entities.

EyeQ evaluates multiple available trust and risk signals rather than relying on a single review, rating or source.

  • Transparency88
  • Reputation82
  • Policies79
  • Legal74
  • Consumer Experience86
  • Security90

Trust Score

1–10

Trust Grade

A–F

The specific signals used can vary depending on the subject and available evidence.

An EyeQ Trust Score should be considered together with the underlying findings, evidence and context presented by ShouldEye.

Read the EyeQ Trust Score methodology

How the assessment comes together

  1. 01

    Evidence

    Relevant publicly available information is identified for the subject.

  2. 02

    Signals

    EyeQ organizes trust and risk indicators from the available evidence.

  3. 03

    Evaluation

    Signals are considered together rather than as a single isolated rating.

  4. 04

    EyeQ Trust Score

    Findings are summarized into a clearer assessment with supporting context.

Multi-Model AI

One Model Doesn't Always Tell the Whole Story.

Different AI models can interpret the same question or information differently.

ShouldEye can use a network of up to 60+ AI models and model-based systems, where applicable, to help analyze information from multiple perspectives.

The models used can vary depending on:

  • selected ShouldEye mode
  • type of question
  • model availability
  • analysis requirements

Not every search sends the prompt to all 60+ models.

AI Modes

Choose How ShouldEye Thinks.

Use one model, compare two, find consensus or look for an additional edge.

Consensus

Find Where AI Agrees.

ShouldEye Consensus Mode compares information and responses across multiple AI models to identify where models agree, where they disagree and which conclusions have broader support.

Consensus Mode is designed to reduce dependence on the output of one AI system by examining multiple perspectives.

From Sources to Findings

Don't Just Show the Answer. Show What Informed It.

ShouldEye is designed to provide context around findings instead of asking users to rely blindly on one AI-generated conclusion.

Where available, ShouldEye can surface relevant information, signals and sources that informed the analysis.

  1. 01

    Source

    Official record

  2. 02

    Information

    Relevant information extracted

  3. 03

    Signal

    Signal identified

  4. 04

    EyeQ Analysis

    Context evaluated

  5. 05

    Finding

    Finding presented to the user

Illustrative example — This example is fictional and does not describe a real allegation.

One Intelligence System

Research More Than Websites.

ShouldEye analyzes publicly available information. It does not claim access to private databases unless that access is independently true for a specific product surface.

The Web Changes

Intelligence Should Change With It.

Companies change. Policies change. Reviews accumulate. Legal proceedings develop. Websites change. New information becomes available.

ShouldEye intelligence can change when the information available about a subject changes.

  1. Analysis
  2. New Information
  3. EyeQ Re-evaluation
  4. Updated Intelligence

ShouldEye does not claim continuous real-time monitoring for every result.

Transparency

Intelligence, Not Blind Trust.

ShouldEye is designed to help users research and understand information, not replace independent judgment.

AI systems can make mistakes. Public information can be incomplete, outdated or incorrect. Sources may disagree, and the absence of negative information does not guarantee that a person, company, website or product is safe or trustworthy.

EyeQ Trust Scores and ShouldEye findings should be considered together with the underlying evidence, sources and context.

Important decisions should be independently verified where appropriate.

ShouldEye at a Glance

Platform
ShouldEye
Intelligence System
EyeQ
Core Assessment
EyeQ Trust Score
AI Approach
Multi-model AI intelligence
Modes
Consensus, Duel, Single, Edge
Research Areas
Companies, people, websites, products, games, scams, messages, brands and services
Information Types
Public web information, policies, records, legal and regulatory information, reviews, complaints, reputation and other relevant signals
Primary Purpose
Help users research trust, risk, reputation and important context

ShouldEye is a multi-model AI search and trust intelligence platform. EyeQ is ShouldEye's intelligence system for analyzing information, trust and risk across multiple web sources and AI systems.

FAQ

How ShouldEye Works

ShouldEye is a multi-model AI search engine and trust intelligence platform designed to help people research and verify companies, websites, people, products, games, scams and other things they encounter online. ShouldEye combines AI analysis with information from across the web to surface useful facts, trust signals, risks and important context before users make decisions.

EyeQ is ShouldEye's AI intelligence system for analyzing trust, risk and information across the web. EyeQ organizes and compares signals from relevant sources and AI systems to help users understand companies, people, websites, products, games, scams and other subjects. EyeQ powers ShouldEye intelligence features including trust assessments, the EyeQ Trust Score and multi-model analysis.

The EyeQ Trust Score is ShouldEye's proprietary trust and risk assessment for companies, websites, products, people, games and other entities. EyeQ evaluates available signals that may include reputation, ownership and transparency, policies, legal and regulatory information, consumer experiences, complaints, security indicators and other relevant evidence. The EyeQ Trust Score is designed to summarize these signals into a clearer assessment while allowing users to review the underlying findings and context.

The EyeQ Trust Score is based on multiple trust and risk signals analyzed by EyeQ. The specific signals used can vary depending on the subject being evaluated, but may include transparency, ownership information, legal activity, regulatory information, consumer feedback, complaints, reputation, security signals, terms, privacy practices and other relevant data. EyeQ considers the available evidence together rather than relying on a single review, rating or source.

ShouldEye analyzes publicly available information from across the web. Depending on the subject, sources may include official websites, company disclosures, terms and privacy policies, public records, legal and regulatory information, news coverage, consumer reviews, complaints, community discussions, social platforms and other relevant online sources. EyeQ can compare information across multiple sources rather than relying on a single source.

Depending on the subject, ShouldEye may analyze public information such as company websites, terms of service, privacy policies, corporate information, consumer reviews, complaints, community discussions, news, regulatory information, legal records, security signals and other relevant online sources.

Different AI models can interpret information differently. ShouldEye can use a network of 60+ AI models and model-based systems to analyze questions and information from multiple perspectives rather than depending entirely on the output of one model. The models and sources used can vary depending on the type of question or analysis.

No. ShouldEye can use a network of up to 60+ AI models and model-based systems where applicable, but the models used depend on the selected ShouldEye mode, the type of question, model availability and analysis requirements. Not every search sends the prompt to all 60+ models.

ShouldEye Consensus Mode compares information and responses across multiple AI models to identify where models agree, where they disagree and which conclusions have broader support. Consensus Mode is designed to reduce dependence on the output of a single AI system by evaluating a question across multiple models and presenting areas of agreement and disagreement.

ShouldEye Duel Mode allows two AI models to evaluate the same question or subject side by side. Duel Mode helps users compare differences in responses, conclusions, reasoning and emphasis between models instead of receiving only one AI perspective.

ShouldEye Single Mode allows users to select and use one AI model for a question or analysis. Single Mode is designed for users who want a direct response from a specific model rather than a multi-model comparison or combined result.

ShouldEye Edge Mode is designed to surface additional angles, risks, opportunities and useful insights that may not appear in a conventional AI response. Edge Mode focuses on identifying context that may give the user a deeper understanding of a subject or reveal considerations that are easy to overlook in a standard answer.

ShouldEye evaluates trust and risk by examining multiple signals rather than relying on a single rating or review. Depending on the subject, EyeQ may consider ownership and transparency, legal and regulatory information, policies, consumer experiences, complaints, reputation, security signals, public records and other relevant evidence. ShouldEye organizes these signals to help users understand both positive indicators and potential risks.

No. Traditional review platforms primarily organize ratings and experiences submitted by users. ShouldEye is designed to analyze a broader set of information that can include reviews as well as policies, company information, public records, legal and regulatory signals, online discussions, security information and other web intelligence.

Traditional search engines primarily help users find webpages. ShouldEye is designed as a trust intelligence layer that combines web research, source analysis and multiple AI models to help users understand trust, risk, reputation and important context about the subject being researched.

Individual AI assistants typically generate an answer using one model or system. ShouldEye can examine information from multiple AI perspectives and organize supporting signals so users can see agreement, disagreement and evidence around a subject rather than depending entirely on one response.

ShouldEye intelligence can change as new information becomes available. New reviews, complaints, policy changes, company developments, legal activity, regulatory information and other signals can affect what EyeQ finds. Individual ShouldEye pages may therefore display updated findings as new information is discovered.

Yes. Because public information changes over time, ShouldEye findings and EyeQ assessments can change when new relevant information becomes available or when earlier signals are no longer current.

No. An EyeQ Trust Score is not a guarantee of safety. It is designed to summarize available trust and risk signals and should be considered together with the underlying findings, evidence and context. The absence of negative information does not guarantee that a person, company, website or product is safe or trustworthy.

Review the supporting sources and context shown with the findings, and independently verify important details before making decisions. Public information can be incomplete, outdated or incorrect, and ShouldEye is designed to help research information rather than replace independent judgment.

See What ShouldEye Finds.

Research companies, people, websites, products, games, scams and more using web intelligence and multiple AI perspectives.