battles / Fraud
NoFraud vs Subuno
NoFraud ($250/mo/mo, vibe code 5/10) vs Subuno ($149/mo/mo, vibe code 6/10). Subuno 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
$149/mo/mo
- MVP
- 1 week
- Full replacement
- 6-12 months, due to third-party API integration maintenance and continuous rule optimization
easier to rebuild
get the build prompt →price gap / year
$1,212/mo
running both / year
$4,788/mo
our call
Start with Subuno — 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
Subuno
Subuno's underlying tech is an IF/THEN rules engine connected to third-party identity/risk lookup services. Rebuilding the UI and rule execution in Node.js is trivial, but maintaining contracts, schema mappings, and API keys for a dozen external fraud vendors is not worth the overhead for most merchants.
you can rebuild
- Custom IF/THEN rule engine for flagging high-risk orders
- Manual order review queue with approve/reject actions
- Email alerts and webhook triggers for flagged transactions
- Basic IP geolocation and address verification (AVS) checks
- Custom merchant-defined whitelists and blacklists
what you lose
- Pre-integrated access to 15+ external fraud data providers
- Unified billing and unified payload normalization across third-party identity APIs
- Cross-merchant shared bad-actor detection network
- Zero-maintenance e-commerce store platform plugins
- Turnkey automated order status updating in connected store platforms
real moats
- Aggregated integration maintenance across a broad mesh of specialized risk APIs
- Cross-merchant shared blacklists and fraud signal history
- Low subscription fee relative to managing multi-vendor API overhead directly
open source escape hatches
- json-rules-engine MIT
- Ruru MIT
- Activepieces MIT
Questions people ask
Which is easier to rebuild with AI, NoFraud or Subuno?
Subuno. It scores 6/10 on vibe code with a moat of 3/10, so an AI-assisted MVP takes about 1 week and a full replacement about 6-12 months, due to third-party API integration maintenance and continuous rule optimization.
Which one costs less, NoFraud or Subuno?
Subuno at $149/mo/mo for a typical mid-market store. The gap between the two is about $1,212/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 Subuno?
Pre-integrated access to 15+ external fraud data providers Unified billing and unified payload normalization across third-party identity APIs Cross-merchant shared bad-actor detection network
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