battles / Fraud
Eye4Fraud vs Sift
Eye4Fraud ($500/mo/mo, vibe code 3/10) vs Sift ($12,500/mo/mo, vibe code 4/10). Eye4Fraud is the easier one to rebuild yourself — here is what you lose either way.
Fraud
$500/mo/mo
- MVP
- 1 week
- Full replacement
- Never — chargeback financial liability cannot be replaced with software
easier to rebuild
get the build prompt →Fraud
$12,500/mo/mo
- MVP
- 2-3 weeks
- Full replacement
- 9-18 months
price gap / year
$144,000/mo
running both / year
$156,000/mo
our call
Start with Eye4Fraud — highest vibe code, weakest moat.
Eye4Fraud
Building a rule engine for fraud scoring in Cursor takes days, but Eye4Fraud's core value is financial insurance and global intelligence. AI cannot write checks to cover $5,000 chargeback disputes when a stolen card slips through custom rules.
you can rebuild
- Basic order risk scoring engine
- Rules-based transaction flagging (AVS, CVV, IP matching)
- Customer order review dashboard for operations staff
- Email notifications for suspicious order holds
- E-commerce platform webhook listeners for pending orders
what you lose
- 100% chargeback guarantee and financial reimbursement
- Cross-merchant network intelligence on stolen identity reuse
- Human fraud analyst manual review service
- Automated dispute handling and representation with banks
- Device fingerprinting database across thousands of stores
real moats
- Financial underwriting capacity to absorb chargeback losses
- Proprietary cross-merchant fraud graph and device telemetry
- Human analyst operations network for edge cases
open source escape hatches
- MaxMind minFraud Node API Apache-2.0
- MindsDB GPL-3.0
- PostHog MIT
Sift
An AI coding agent can write a custom rule engine, device fingerprinting intake, and XGBoost fraud scoring API in a couple of weeks. However, you cannot replicate Sift's global data network, which uses cross-merchant behavioral signals across 34,000+ sites to stop fraud on arrival.
you can rebuild
- Client-side JS snippet integration for basic device signal capture
- Custom rule builder for block/allow lists (e.g., country code matching, velocity limits)
- Real-time scoring API endpoint returning risk numbers (0-100)
- Manual investigation review queue console for fraud analysts
- Shopify and Magento webhook trigger integrations
what you lose
- Access to Sift's global consortium data tracking over 1 billion unique digital personas
- Pre-trained cross-merchant Account Takeover (ATO) and identity theft detection models
- Sift ActivityIQ generative AI pattern detection across global network events
- Out-of-the-box integrations with major enterprise processors (Adyen, Stripe, PayPal) and platforms
- Automated continuous machine learning retraining on global chargeback data
real moats
- Global Consortium Network: Shared signal intelligence across thousands of global enterprises processing 70B+ events monthly.
- Petabyte-Scale Behavioral Graph: Historical link analysis linking IPs, device hashes, credit card bins, and shipping addresses across decades.
- Zero-Day Fraud Vector Detection: Ability to detect novel botnet and account takeover patterns before individual merchants experience them.
open source escape hatches
- FraudLabs / open rules engines (Drools) Apache-2.0
- Feedzai alternatives — River BSD-3
- MaxMind minFraud open clients Apache-2.0
Questions people ask
Which is easier to rebuild with AI, Eye4Fraud or Sift?
Eye4Fraud. It scores 3/10 on vibe code with a moat of 6/10, so an AI-assisted MVP takes about 1 week and a full replacement about Never — chargeback financial liability cannot be replaced with software.
Which one costs less, Eye4Fraud or Sift?
Eye4Fraud at $500/mo/mo for a typical mid-market store. The gap between the two is about $144,000/mo a year.
What do I lose if I replace Eye4Fraud?
100% chargeback guarantee and financial reimbursement Cross-merchant network intelligence on stolen identity reuse Human fraud analyst manual review service
What do I lose if I replace Sift?
Access to Sift's global consortium data tracking over 1 billion unique digital personas Pre-trained cross-merchant Account Takeover (ATO) and identity theft detection models Sift ActivityIQ generative AI pattern detection across global network events
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