A Clearer View of Trust and Risk.

Our Approach

Trust Is Not One Signal.

A review score is one signal. A legal record is one signal. A privacy policy is one signal. A complaint is one signal. A security indicator is one signal. None of these should automatically define the whole picture.

EyeQ is designed to evaluate multiple relevant signals together and provide a clearer summary of the available evidence.

What the Score Means

A Summary of the Available Trust Picture.

The EyeQ Trust Score is a ShouldEye assessment designed to summarize relevant trust and risk signals available for a subject at the time of analysis.

The score is intended to help users quickly understand whether available information presents stronger trust signals, meaningful uncertainty or potential areas of concern.

It is not:

• a guarantee of safety
• a guarantee of legitimacy
• a legal conclusion
• a prediction of future behavior
• a substitute for underlying evidence

Signal Categories

Different Subjects Require Different Evidence.

EyeQ does not apply an identical checklist to every company, person, website, product or game. The relevant evidence depends on what is being evaluated and what reliable information is available.

• Ownership & Transparency

  Available information about who operates, owns or is responsible for an entity.

• Terms & Policies

  Terms of service, privacy policies, refund policies and other relevant rules.

• Legal Information

  Relevant publicly available legal proceedings, disputes and records.

• Regulatory Information

  Relevant government, licensing and regulatory information.

• Consumer Experiences

  Reviews, complaints and publicly shared experiences.

• Reputation

  Patterns across available public information that may affect trust.

• Security Signals

  Relevant website, technical or security-related information where available.

• Company & Public Information

  Official disclosures, company information and other public records.

• News & Media

  Relevant reporting and published information.

• Community Discussions

  Relevant public discussion across forums, communities and social platforms.

Not every category applies to every subject, and not every available source is treated as equally reliable or relevant.

Source Quality

Not Every Source Carries the Same Weight.

ShouldEye considers the nature and quality of the source when evaluating available information.

• Primary / Official Evidence

  Government records, regulators, courts, official filings, company disclosures and original policies.

• Established Secondary Sources

  Credible published reporting and other reliable secondary information.

• Consumer Experience Sources

  Reviews, complaints and first-person experiences.

• Community & Social Signals

  Public discussions that may reveal patterns or context but can be incomplete or unverified.

Evidence Analysis

Context Matters More Than Raw Counts.

• A large number of complaints does not automatically mean an entity is high risk.
• A single legal proceeding does not automatically mean an entity is untrustworthy.
• A high review rating does not automatically mean an entity is safe.

EyeQ is designed to consider context.

Potential contextual factors can include:

• source quality
• relevance
• recency
• severity
• consistency across sources
• whether evidence is verified or disputed
• whether the signal appears isolated or part of a broader pattern

1. 01

   Signal

2. 02

   Context

3. 03

   Relevance

4. 04

   Cross-Check

5. 05

   Assessment

Cross-Checking

One Source Should Not Tell the Whole Story.

Where possible, EyeQ is designed to compare information across multiple sources rather than relying on one webpage, review platform, complaint or AI-generated statement.

When sources agree, confidence in a finding may increase. When sources conflict, the disagreement itself can become important context.

AI-Assisted Analysis

AI Helps Analyze the Evidence. It Does Not Replace the Evidence.

EyeQ uses AI to help organize, compare and interpret available information, but the presence of an AI-generated conclusion does not make the underlying evidence more reliable.

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

Different models may:

• emphasize different signals
• interpret ambiguity differently
• reach different conclusions
• identify different risks or context

ShouldEye’s multi-model approach is designed to make these differences more visible rather than pretending one model is always correct.

The Process

How an EyeQ Assessment Is Built.

1. 01

   Gather Relevant Information

   ShouldEye identifies information relevant to the subject being evaluated.

2. 02

   Organize the Evidence

   EyeQ groups information into relevant trust and risk signals.

3. 03

   Evaluate Context

   Signals are considered using factors such as source quality, relevance, recency, severity and consistency.

4. 04

   Cross-Check Findings

   Where possible, information is compared across sources and AI perspectives.

5. 05

   Produce the Trust Assessment

   EyeQ summarizes the available evidence into a Trust Score and supporting findings.

Methodology Integrity

Transparent Principles. Protected Scoring Logic.

ShouldEye believes users should understand what an EyeQ Trust Score represents and the types of evidence that can influence an assessment.

At the same time, publishing every internal weighting, threshold and scoring rule could make the system easier to manipulate.

For that reason, ShouldEye publicly explains the principles, signal categories and evidence approach behind EyeQ while keeping certain scoring mechanics, weighting systems, abuse protections and internal evaluation logic proprietary.

Interpreting the Score

What Different EyeQ Scores Mean.

EyeQ Trust Scores are shown on a 0–10 scale. On company surfaces, letter grades are derived from those scores to help users scan the assessment quickly.

• A · 9.0–10.0

  Stronger trust signals

  Available information presents comparatively stronger trust signals based on the evidence EyeQ could evaluate at the time of analysis.

• B · 8.0–8.9

  Generally positive

  Available information is generally positive, with fewer material concerns relative to subjects in lower bands.

• C · 7.0–7.9

  Mixed or uncertain

  Available information presents mixed signals, meaningful uncertainty or a less clear overall trust picture.

• D · 6.0–6.9

  Elevated concerns

  Available information points to elevated concerns that deserve closer review of the underlying findings and evidence.

• F · Below 6.0

  Significant risk indicators

  Available information indicates significant risk indicators or weaker trust signals relative to higher-scoring subjects.

Letter grades appear on company surfaces derived from EyeQ Trust Scores. They are decision-support labels, not a guarantee of safety, legitimacy or future behavior.

Balanced Analysis

EyeQ Looks for Positive Signals Too.

Trust analysis should not focus only on problems. EyeQ is designed to consider positive, neutral and negative information where relevant.

The presence of one positive or negative signal does not necessarily determine the overall assessment.

Freshness

Trust Scores Can Change.

• Companies change.
• Websites change ownership.
• Policies change.
• Reviews accumulate.
• Complaints are resolved.
• Legal proceedings develop.
• Regulatory information changes. Security issues can appear or be fixed.

Because the underlying evidence can change, an EyeQ Trust Score may change too.

1. Original Assessment
→
2. New Information
→
3. EyeQ Re-evaluation
→
4. Updated Score

Where appropriate, ShouldEye pages should display when important information was last analyzed or updated.

Uncertainty

No Data Is Not the Same as Good Data.

The absence of negative information does not automatically mean an entity is trustworthy.

Likewise, limited information can make a strong conclusion difficult.

Where appropriate, EyeQ should distinguish between:

• Positive evidence

  Available information supports comparatively stronger trust signals.

• Negative evidence

  Available information points to concerns, weaker trust signals or elevated risk indicators.

• Conflicting evidence

  Relevant sources disagree, and the disagreement itself becomes part of the assessment.

• Insufficient evidence

  Too little reliable information is available to support a strong conclusion.

Conflicting Information

Sometimes the Evidence Disagrees.

Public information is not always consistent.

A company may describe an event differently from consumers.

Different publications may report different facts.

Records can change.

Reviews can be misleading or fraudulent.

When relevant sources conflict, EyeQ is designed to consider the disagreement rather than automatically selecting whichever source supports the strongest conclusion.

Limitations

A Score Is Intelligence, Not Certainty.

AI systems can make mistakes. Public records can be incomplete. Consumer reports can be inaccurate. Sources can become outdated. Identity matching can be imperfect.

For these reasons, the EyeQ Trust Score should be used as a research and decision-support tool, not as a guarantee or definitive statement of fact about future behavior.

For important legal, financial, medical, employment, housing, safety or other consequential decisions, users should independently verify critical information and use qualified professional advice where appropriate.

Corrections

Better Evidence Should Improve the Assessment.

If relevant information is inaccurate, outdated or incomplete, new evidence may affect a ShouldEye finding or EyeQ Trust Score.

ShouldEye is working toward clearer processes for reporting potentially inaccurate or outdated information.

The Score Is the Start

Don't Stop at the Number.

1. 01

   EyeQ Trust Score

   The quick summary.

2. 02

   Key Findings

   The most important signals.

3. 03

   Evidence

   Information supporting those findings.

4. 04

   Sources

   Where available information originated.

5. 05

   Context

   What users should understand before deciding.

ShouldEye is designed to help users move from a simple score into the evidence and context behind it.

EyeQ Methodology at a Glance

Assessment

EyeQ Trust Score

Platform

ShouldEye

Purpose

Summarize available trust and risk signals

Possible Signal Types

Ownership, transparency, policies, legal information, regulatory information, consumer experiences, reputation, security and other relevant evidence

Source Approach

Multiple relevant sources where available

AI Approach

AI-assisted source and signal analysis with multi-model capabilities

Freshness

Assessments may change when underlying information changes

Score Interpretation

Decision-support intelligence, not a guarantee

Proprietary Elements

Exact weights, formulas, thresholds, anti-gaming systems and internal model orchestration are not publicly disclosed

The EyeQ Trust Score is ShouldEye’s proprietary assessment of trust and risk signals. EyeQ evaluates multiple types of available evidence and context rather than relying on a single review, rating, source or AI response.