battles / Fraud
Fou Analytics vs Subuno
Fou Analytics ($499/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
$499/mo/mo
- MVP
- 2 weeks
- Full replacement
- 12-24 months, due to evolving bot evasion strategies and threat intelligence upkeep
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
$4,200/mo
running both / year
$7,776/mo
our call
Start with Subuno — highest vibe code, weakest moat.
Fou Analytics
While creating a client-side JS beacon and telemetry dashboard with AI takes days, ad fraud detection relies on continuously updated threat models and bot databases. A self-built alternative will catch basic headless browsers but fail against residential proxy networks and stealth botnets.
you can rebuild
- Client-side JS event tracking beacon
- Basic browser detection heuristics (User-Agent parsing, headless browser flags)
- Traffic breakdown dashboards by device, referrer, and UTM parameters
- CSV and S3 automated log exports
- UTM parameter validation and link parameter tracking
what you lose
- Dr. Augustine Fou's proprietary fraud heuristics and pattern recognition algorithms
- Real-time cross-referencing against global residential proxy and datacenter IP databases
- Benchmarked invalid traffic (IVT) baselines across billions of ad impressions
- Audit-ready evidence logs formatted for ad network refund disputes
- Ongoing counter-measures against zero-day fingerprint evasion frameworks
real moats
- Proprietary dataset of invalid traffic signatures and ad fraud patterns
- Cross-merchant network effects for rapid identification of emerging botnets
- Expert reputation and audit-grade credibility in digital media supply disputes
open source escape hatches
- BotD Apache-2.0
- Matomo GPL-3.0
- Plausible Analytics AGPL-3.0
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, Fou Analytics 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, Fou Analytics or Subuno?
Subuno at $149/mo/mo for a typical mid-market store. The gap between the two is about $4,200/mo a year.
What do I lose if I replace Fou Analytics?
Dr. Augustine Fou's proprietary fraud heuristics and pattern recognition algorithms Real-time cross-referencing against global residential proxy and datacenter IP databases Benchmarked invalid traffic (IVT) baselines across billions of ad impressions
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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