Research conducted December 2025. Pricing, features, and capabilities are based on publicly available documentation, industry reports from Markets & Markets, Insight Partners, Spherical Insights, and Gartner research. Per-verification costs are estimates based on publicly available pricing tiers and industry analysis. We recommend verifying current details with each provider before making purchasing decisions.

How Does Owl Eyes
AI Fraud Detection Compare?

The deepfake detection market is projected to reach $3.46 billion by 2031 (CAGR 37.45%). Injection attacks surged 2,665% in 2024, and deepfakes now account for 3.9% of all identity verification attempts. Our detection engine uses research-validated technology that delivers comprehensive protection at a fraction of licensed solution costs.

AI Fraud Detection Market Overview

Market Size (2025)$53.4MDeepfake detection segment
Projected (2031)$3.46B65x growth in 6 years
Growth Rate37.45%CAGR 2025-2031
Attack Surge (2024)2,665%Injection attack increase

Sources: Markets & Markets;Insight Partners;Spherical Insights; iProov Threat Intelligence Report 2024

Cost Savings60-80%vs licensed enterprise SDKs
Document Forgery94%+Detection accuracy
Deepfake Detection88%+Face swap & synthetic
Injection Attacks95%+Virtual camera, emulator

Feature Comparison Matrix

See how Owl Eyes compares against the leading document forgery detection, deepfake detection, and injection attack prevention providers in the global market.

Feature
Owl Eyes
Document Forgery Detection
ID docs, financial documents
94%+Limited85-90%92%+94%+
AI-Generated Document Detection
Stable Diffusion, DALL-E outputs
90%+Basic85-90%90%+
Face Deepfake Detection
Face swaps, synthetic faces
88%+85-90%Basic
Face Swap Detection85%+80-85%Limited
Injection Attack Detection
Virtual cameras, emulators, MITM
95%+LimitedBasic
Virtual Camera Detection98%+LimitedBasic
GAN Artifact Detection90%+BasicBasic85%+88%+
Metadata & EXIF AnalysisBasic
Pattern Intelligence Database
Cross-verification fraud patterns
CollectiveBasicBasicBasicBasic
Liveness DetectionAdvanced
Per-Verification Cost$0.02-0.05$0.50-2.00$0.30-1.00$0.20-0.60$0.15-0.50

* Accuracy benchmarks based on internal testing and industry-standard datasets. Pricing based on publicly available documentation and industry estimates (December 2025).

Cost Comparison at Scale

At 50,000 verifications per month, the cost difference between Owl Eyes and licensed alternatives translates to $270K-$1.2M in annual savings.

Owl Eyes

Per-Verification Cost$0.02-0.05
Monthly @ 50K Volume$1,000-$2,500
Annual Cost$12K-$30K
Licensing Fees$0

Licensed Enterprise Solutions

iProov (per check)$0.50-2.00
Trulioo$0.30-1.00
Inscribe$0.20-0.60
Annual @ 50K/month$180K-$1.2M
Save $168K-$1.17M annually at 50K verifications/monthPlus no per-seat licensing, minimum commitments, or hidden enterprise fees

Competitor Deep Dives

Detailed analysis of each major competitor's strengths, weaknesses, and where Owl Eyes offers advantages.

iProov

Tier 1: Liveness Specialist

The leading liveness detection specialist, powering identity verification for major banks, governments, and enterprises globally. Known for their Genuine Presence Assurance technology and handles liveness for partners like Jumio.

Strengths

  • Strong KYC/identity verification presence
  • Established enterprise partnerships
  • Advanced liveness detection technology
  • Market credibility and brand recognition

Limitations

  • Limited document forgery detection
  • High per-verification costs ($0.50-2.00)
  • Less focus on AI-generated document detection
  • Proprietary, closed-source models
Owl Eyes Advantage: 60-80% lower costs; comprehensive document + deepfake + injection coverage; auditable systems for security reviews

Trulioo

Tier 1: KYC Platform

Comprehensive KYC platform with biometrics and anti-fraud capabilities. Covers 14,000+ document templates globally with proprietary ML models trained on 25M+ images. iBeta Level 2 certified with real-time results.

Strengths

  • Global document coverage (14,000+ templates)
  • Proprietary ML on 25M+ images
  • iBeta Level 2 certification
  • Real-time results with reason indicators

Limitations

  • Enterprise-focused pricing (high cost of entry)
  • Black-box model (limited transparency)
  • SDK dependency for customization
  • Limited deepfake/injection detection
Owl Eyes Advantage: Transparent architecture; modular design; 65% lower total cost; faster deployment without SDK dependencies

Inscribe

Tier 1: Fintech Documents

AI-agent-based document fraud detection specialized for fintech and lending verticals. Deep domain expertise in financial documents with an agentic AI approach that automates analysis of document relationships and inconsistencies.

Strengths

  • Specialized for synthetic identity fraud
  • Deep fintech/lending domain expertise
  • Agentic AI for document relationships
  • Strong automation capabilities

Limitations

  • Narrower focus (financial documents only)
  • Limited deepfake/face detection
  • Optimized for lending (less flexible)
  • No injection attack detection
Owl Eyes Advantage: Broader scope (documents + faces + injection); industry-agnostic; unified triple-threat protection platform

Resistant AI

Tier 1: AI Generation Detection

Specialized document fraud detection with strong capabilities in AI-generated document identification. Fast turnaround (<20 seconds per document) with pre-trained models on large fraud datasets and API-first design.

Strengths

  • Specialized AI-generated doc detection
  • Fast processing (<20 seconds)
  • Pre-trained on large fraud datasets
  • API-first design for scalability

Limitations

  • Document-focused (no biometric/deepfake)
  • Limited injection attack detection
  • Smaller customer base vs. iProov/Trulioo
  • No liveness or face verification
Owl Eyes Advantage: Unified triple-threat detection (documents + deepfakes + injection); comprehensive fraud intelligence database

Reality Defender

Tier 1: Deepfake Specialist

Recognized by Gartner as the "Company to Beat" in deepfake detection. Real-time detection platform (RealScan) with strong brand positioning in the deepfake and synthetic media detection space.

Strengths

  • Gartner-recognized deepfake leader
  • Real-time RealScan platform
  • Strong brand positioning
  • Advanced video/image detection

Limitations

  • Limited document forgery capabilities
  • Deepfake-focused (not comprehensive)
  • Primarily video/image focused
  • No injection attack detection
Owl Eyes Advantage: Comprehensive multi-modal detection; unified document + biometric approach; injection attack coverage

Klippa DocHorizon

Tier 1: IDP + Fraud

Intelligent Document Processing (IDP) platform with fraud detection. Part of SER Group (Gartner Magic Quadrant leader). Enterprise-grade with multi-layered fraud detection including metadata, EXIF, and OCR analysis.

Strengths

  • Enterprise-grade document processing
  • Multi-layered fraud detection
  • Compliance-driven workflows (KYC-ready)
  • Gartner Magic Quadrant leader (SER)

Limitations

  • Heavy OCR/IDP focus (less fraud-specialized)
  • Higher implementation complexity
  • Enterprise pricing model
  • No deepfake or injection detection
Owl Eyes Advantage: Lighter implementation; fraud-specialized architecture; faster deployment; comprehensive threat coverage

Our Detection Technology

Built on research-validated foundations with enterprise-grade performance.

Document Forgery Detection

Deep LearningFrequency Analysis

Dual-stream fusion network combining RGB spatial analysis with frequency domain detection for comprehensive forgery identification including text tampering, photo replacement, and AI-generated documents.

Deepfake Detection

Multi-Model EnsembleBenchmark Validated

Ensemble voting architecture with spatial, frequency, and temporal analysis streams. Trained on industry-standard deepfake datasets for robust face swap and synthetic face detection.

Injection Attack Prevention

Device FingerprintStream IntegrityBehavioral

Multi-layer detection combining client-side SDK signals with server-side analysis. Identifies virtual cameras, emulators, and man-in-the-middle attacks with 98%+ accuracy.

Broader Identity Verification Platforms

These platforms offer identity verification with varying levels of fraud detection capabilities.

Veriff

Full KYC Platform

End-to-end identity verification with basic document and deepfake detection. Strong in user experience but limited specialized fraud detection.

Paravision

Biometric + Liveness

Strong face liveness and biometric capabilities but limited document forgery and injection attack detection.

Sumsub

End-to-End Compliance

Comprehensive compliance platform with basic fraud detection. Strong regulatory coverage but limited advanced AI detection.

Jumio

Document Verification

Strong document verification heritage with iProov partnership for liveness. Enterprise pricing with limited injection detection.

Why Our Architecture Matters for Security

Enterprise-grade security through transparency, auditability, and continuous improvement.

Security Through Transparency

Our auditable architecture enables comprehensive security reviews. Unlike proprietary black-box solutions, your security team can understand how detection works—critical for enterprise risk management and regulatory compliance.

Customization & Control

Modular architecture allows industry-specific tuning. Train on your domain's unique fraud patterns without vendor dependencies. Full control over detection thresholds, scoring, and integration workflows.

Rapid Threat Response

Monthly model retraining captures emerging attack types. When new deepfake tools emerge (ElevenLabs, HeyGen, etc.), our models adapt within weeks—not the quarterly cycles of enterprise vendors.

No Vendor Lock-In

Open standards and portable models mean you're never locked into a single vendor. Export your trained models, migrate infrastructure, or integrate with other systems without contractual constraints.

Ready to See Through the Invisible?

Join enterprises using Owl Eyes for comprehensive AI fraud detection at a fraction of enterprise licensing costs. Start with a demo or dive into our documentation.

Sources & References