battles / Fraud

Subuno vs Vesta

Subuno ($149/mo/mo, vibe code 6/10) vs Vesta ($1,500/mo/mo, vibe code 3/10). Subuno is the easier one to rebuild yourself — here is what you lose either way.

NICHE

Fraud

$149/mo/mo

Vibe code6/10
Moat3/10
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 →
KEEP

Fraud

$1,500/mo/mo

Vibe code3/10
Moat8/10
MVP
1 week
Full replacement
Never, due to chargeback financial underwriting and proprietary global risk network
get the build prompt →

price gap / year

$16,212/mo

running both / year

$19,788/mo

our call

Start with Subuno — highest vibe code, weakest moat.

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

Vesta

While building a device fingerprint collector and rule-based risk dashboard takes days, Vesta's core offering is zero-liability financial guarantees and cross-merchant network signals. AI agents cannot generate financial underwriting balance sheets or billions of historical fraud data points.

you can rebuild

  • Basic rule-based risk scoring engine (velocity, country blocklists)
  • Client-side device fingerprinting collector script
  • Order approval and rejection queue for manual review
  • IP geolocation, proxy, and VPN detection API integration
  • Threshold-based 3D Secure dynamic triggers

what you lose

  • 100% zero-liability chargeback reimbursement guarantee
  • Cross-merchant consortium dataset tracking fraudsters across thousands of stores
  • Machine learning models trained on billions of historical card transactions
  • Automated chargeback evidence submission and dispute handling
  • Dedicated fraud analyst teams and custom enterprise risk models

real moats

  • Financial balance sheet supporting chargeback indemnification
  • Global cross-merchant graph dataset linking identities, devices, and cards
  • Proprietary ML models trained on real-world dispute outcomes

open source escape hatches

Questions people ask

Which is easier to rebuild with AI, Subuno or Vesta?

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, Subuno or Vesta?

Subuno at $149/mo/mo for a typical mid-market store. The gap between the two is about $16,212/mo a year.

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

What do I lose if I replace Vesta?

100% zero-liability chargeback reimbursement guarantee Cross-merchant consortium dataset tracking fraudsters across thousands of stores Machine learning models trained on billions of historical card transactions

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