battles / Fraud
Sift vs Subuno
Sift ($12,500/mo/mo, vibe code 4/10) 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
$12,500/mo/mo
- MVP
- 2-3 weeks
- Full replacement
- 9-18 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
$148,212/mo
running both / year
$151,788/mo
our call
Start with Subuno — highest vibe code, weakest moat.
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
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, Sift 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, Sift or Subuno?
Subuno at $149/mo/mo for a typical mid-market store. The gap between the two is about $148,212/mo a year.
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
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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