battles / Fraud
NoFraud vs Sift
NoFraud ($250/mo/mo, vibe code 5/10) vs Sift ($12,500/mo/mo, vibe code 4/10). NoFraud is the easier one to rebuild yourself — here is what you lose either way.
Fraud
$250/mo/mo
- MVP
- 2-3 weeks
- Full replacement
- 12-18 months
easier to rebuild
get the build prompt →Fraud
$12,500/mo/mo
- MVP
- 2-3 weeks
- Full replacement
- 9-18 months
price gap / year
$147,000/mo
running both / year
$153,000/mo
our call
Start with NoFraud — highest vibe code, weakest moat.
NoFraud
NoFraud (Wyllo) is fundamentally an insurance product wrapped in an API. While the order scoring and Shopify tagging features can be cloned with standard LLM tools in a couple of weeks, you cannot write code that underwrites thousands of dollars in credit card chargebacks.
you can rebuild
- Automated order risk scoring based on standard rules (IP, distance, proxy, email).
- Shopify order tagging and automatic cancellation API triggers.
- Manual order review dashboard with signal visualizations.
- Basic velocity and heuristic-based risk engine.
what you lose
- 100% financial reimbursement guarantee on fraudulent chargebacks passed by the engine.
- 24/7 human analyst team conducting manual order reviews on borderline transactions.
- Network-level risk detection trained on shared cross-merchant fraud signals.
- Direct chargeback dispute handling and representment operations.
real moats
- Balance sheet capital to guarantee chargeback reimbursements at scale.
- Operational infrastructure of human fraud analysts performing 24/7 manual reviews.
- Consolidated network intelligence across thousands of high-volume e-commerce storefronts.
open source escape hatches
- FraudLabs / open rules engines (Drools) Apache-2.0
- Feedzai alternatives — River BSD-3
- MaxMind minFraud open clients Apache-2.0
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, NoFraud or Sift?
NoFraud. It scores 5/10 on vibe code with a moat of 7/10, so an AI-assisted MVP takes about 2-3 weeks and a full replacement about 12-18 months.
Which one costs less, NoFraud or Sift?
NoFraud at $250/mo/mo for a typical mid-market store. The gap between the two is about $147,000/mo a year.
What do I lose if I replace NoFraud?
100% financial reimbursement guarantee on fraudulent chargebacks passed by the engine. 24/7 human analyst team conducting manual order reviews on borderline transactions. Network-level risk detection trained on shared cross-merchant fraud signals.
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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