DISPEL.CLOUD
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Truth infrastructure for the AI era

Dispel the fog.
See what's real.

Dispel helps evaluate suspicious images, video, voice, music, text, messages, and digital artifacts using provenance, synthetic indicators, scam patterns, and evidence-backed trust scoring.

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ORIGIN Human / AI / Mixed / Unknown
TRUST Evidence-backed scoring
ACTION Clear next-step guidance
PROVENANCE
SCAM RISK
CLAIMS
MANIPULATION
TRUST IS NOW A TECHNICAL PROBLEM

Noise becomes signal. Suspicion becomes evidence. Evidence becomes action.

Origin Manipulation Provenance Scam Risk Claims Action
FOG TO CLARITY

From suspicious input to actionable verdict.

01

Inspect

Dispel ingests suspicious content across text, image, video, voice, music, screenshots, links, and messages.

02

Correlate

Signals are mapped across provenance, synthetic indicators, persuasion patterns, contradictions, and source mismatch.

03

Resolve

A calibrated verdict condenses complexity into a readable trust score, evidence list, and recommended action.

LIVE VERDICT MODEL

Messy input - structured evidence - clear action

Dispel does not read minds. It reads signals.

SUSPICIOUS TRUST SCORE 34
  • Urgency pattern detected
  • Payment pressure language present
  • Provenance missing
  • Identity claim unsupported
Recommended action: Do not pay. Verify independently.
MULTI-MODAL

One trust layer across every suspicious surface.

Text
Image
Video
Voice
Music
Screenshot
Link
Invoice
Chat
SCAM THEATER

See how deception looks before it resolves.

Fake recruiter email

Urgent onboarding, identity requests, and pressure to pay for equipment upfront.

  • Authority impersonation pattern
  • Payment red flag
  • Domain/source mismatch

Cloned emergency voice call

An emotional plea to send money immediately with no verifiable source trail.

  • Urgency spike
  • Identity unverifiable
  • Provenance absent

Fake marketplace seller

Manipulated product photos, pressure to pay off-platform, and inconsistent story details.

  • Manipulation risk signals
  • Off-platform payment request
  • Claim inconsistency

Crypto bait ad

Celebrity-style hype, guaranteed upside language, and unverifiable origin.

  • Scam persuasion pattern
  • Synthetic promotional tone
  • Unsupported claim set
EVIDENCE ENGINE

Dispel does not read minds. It reads signals.

Metadata & provenance

When origin markers exist, Dispel uses them. When they are missing, it says so.

Synthetic indicators

Media and language patterns are evaluated conservatively, never marketed as magical certainty.

Scam patterns

Urgency, coercion, authority signals, payment pressure, and known deception structures are surfaced clearly.

Claim consistency

Unsupported or contradictory claims are flagged so users can verify before acting.

PRODUCT SURFACES

The interface for digital truth.

ANALYSIS

Verdict-first result experience

HISTORY

Saved investigations

REPORT

Shareable trust receipt

API

Programmatic trust scoring for platforms and teams

TRUST ARCHITECTURE

Consumer clarity. Enterprise credibility.

Built for normal users who need answers fast, and structured enough for product surfaces, creator protection, moderation, and trust & safety workflows. 

{
  "verdict": "SUSPICIOUS",
  "overallTrustScore": 34,
  "provenanceScore": 12,
  "scamRiskScore": 78,
  "recommendedAction": "Do not pay"
}
PRICING

Access. Protection. Infrastructure.

FREE

$0

Core access for individual checks.

PLUS

$19

Protection for higher-volume personal use.

PRO

$49

Infrastructure for creators, teams, and platforms.

FAQ

Clarity over hype.

Can Dispel prove something is fake?

No. It evaluates evidence and signals, then explains what is strong, weak, or unknown.

Does it detect lies?

No. Dispel analyzes signals, provenance, manipulation indicators, scam patterns, and claim consistency.

What does “Unknown” mean?

It means the evidence is not strong enough to make a confident call.

FINAL CONVERSION

Truth, before trust.

Verify before you trust, share, or pay.

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