battles / Fraud
NoFraud vs Trustfull
NoFraud ($250/mo/mo, vibe code 5/10) vs Trustfull ($2,500/mo/mo, vibe code 5/10). Trustfull 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
Fraud
$2,500/mo/mo
- MVP
- 2-3 weeks
- Full replacement
- 6-9 months
easier to rebuild
get the build prompt →price gap / year
$27,000/mo
running both / year
$33,000/mo
our call
Start with Trustfull — 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
Trustfull
AI can write a full-featured risk rule engine and signal aggregation service in a afternoon. However, you cannot easily replicate Trustfull's underlying access to direct mobile carrier networks, HLR lookups, and global breach databases without paying high third-party data fees.
you can rebuild
- Custom risk scoring rule builder and threshold evaluation engine.
- Basic IP risk lookup (VPN/Tor/Proxy detection via public databases).
- Email syntactical analysis, disposable domain checks, and MX record verification.
- Redis-based velocity tracking for identity fields (e.g., requests per phone number per hour).
- Audit logging and structured API response formatting.
what you lose
- Direct access to real-time mobile network operator (HLR/SS7) data without setting up separate vendor contracts.
- Cross-merchant global reputation data on fraudulent phone numbers and email addresses.
- Unified billing and SLA management for multi-signal data sources.
- Pre-built compliance workflows for European privacy standards (GDPR) regarding identity lookups.
real moats
- Proprietary integrations and wholesale volume rates with international HLR/telecom data aggregators.
- Aggregated historical data on phone/email reputation built across millions of evaluation requests.
- Low-latency global API infrastructure serving unified risk responses under 100ms.
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 Trustfull?
Trustfull. 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 6-9 months.
Which one costs less, NoFraud or Trustfull?
NoFraud at $250/mo/mo for a typical mid-market store. The gap between the two is about $27,000/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 Trustfull?
Direct access to real-time mobile network operator (HLR/SS7) data without setting up separate vendor contracts. Cross-merchant global reputation data on fraudulent phone numbers and email addresses. Unified billing and SLA management for multi-signal data sources.
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