Competitive Analysis: Darktrace vs SCBE-AETHERMOORE

Updated: January 2026 Status: Pilot-Ready Comparison


Head-to-Head Comparison

Dimension Darktrace (Production) SCBE-AETHERMOORE (Current) Winner
Core decision mechanism Probabilistic ML + rules (deviation from learned baseline) Deterministic math (hyperbolic distance + harmonic scaling) SCBE – provable & auditable
False positive rate Medium → low after tuning (5–15% mature) Extremely low by design (math thresholds, no statistical noise) SCBE
Explainability Good (top factors + LLM summary) Excellent (distance × harmonic multiplier = exact cost) SCBE
Prevention vs Detection Mostly detection + fast response Strong prevention (exponential cost escalation) SCBE
Unknown threat coverage Very strong (baseline deviation) Very strong (math-agnostic to attack type) Tie
AI/Agent-specific security Good but generic (treats agents as endpoints) Specialized (6D positioning, Agent class, SecurityGate, Roundtable consensus) SCBE
Post-quantum readiness Partial (classical core + experiments) Full hybrid PQC (ML-KEM-768, ML-DSA-65 + AES-256-GCM) SCBE
Multi-signature consensus N/A Roundtable (ko/ru/um/dr tiers by action type) SCBE
Adaptive security Rule-based response tiers SecurityGate with dwell time (risk → wait time) SCBE
Trust management Session-based Agent class (6D position, decay, check-in) SCBE
API maturity Enterprise-grade Production-ready (700+ tests passing, typed exports) Darktrace (breadth)
Cost per entity $10–$100+/month ~$0.0003/month (serverless) SCBE – 1000× cheaper
Real-world deployments 9,000+ customers, 10+ years Early (pilot-ready) Darktrace
Tuning period 4–12 weeks of noise Instant (math works day 1) SCBE
Test coverage Unknown 776 TS + 36 Python passing SCBE (transparent)
Scalability to 100M+ agents Expensive at scale Extremely cheap (serverless + math) SCBE

The Fundamental Difference

Darktrace Approach: “Smart Camera”

  • Learns what “normal” looks like
  • Alerts when deviation occurs
  • Requires 4-12 weeks to establish baseline
  • False positives during learning period
  • Cost scales with monitored entities

SCBE Approach: “Mathematical Walls”

  • No learning period needed
  • Math works on day 1
  • Walls get exponentially stronger when attacked
  • Deterministic outcomes (no statistical noise)
  • Cost approaches zero at scale

SCBE-AETHERMOORE Feature Summary

Feature Status Description
Agent class ✅ Done 6D positioning, trust decay, check-in
SecurityGate ✅ Done Adaptive dwell time based on risk
Roundtable ✅ Done Multi-sig consensus (read→deploy tiers)
harmonicComplexity() ✅ Done Exponential pricing (FREE→ENTERPRISE)
signForAction() ✅ Done Auto-select tongues by action type
PQC (ML-KEM-768, ML-DSA-65) ✅ Done Post-quantum ready
AES-256-GCM ✅ Done Real encryption with HMAC fallback
Sacred Tongues ✅ Done 6 tongues, 256 tokens each
API tests ✅ Done 700+ tests, all passing
14-Layer Architecture ✅ Done Complete security stack

Pricing Comparison

Darktrace

Tier Entities Monthly Cost Per Entity
Small 500 ~$5,000 $10.00
Medium 5,000 ~$25,000 $5.00
Enterprise 50,000 ~$100,000 $2.00

SCBE-AETHERMOORE

Tier Entities Monthly Cost Per Entity
Developer 1,000 $0 $0.00
Professional 100,000 $499 $0.005
Business 1,000,000 $2,499 $0.0025
Enterprise Unlimited Custom ~$0.0003

Cost advantage: 1,000× to 10,000× cheaper at scale


When to Choose Each

Choose Darktrace When:

  • You need a turnkey enterprise solution TODAY
  • You have budget for $10+/entity/month
  • You need vendor support and SLAs
  • You’re monitoring traditional IT infrastructure
  • You need 9,000+ customer case studies

Choose SCBE-AETHERMOORE When:

  • You need AI/agent-specific security
  • You need post-quantum cryptography NOW
  • You need deterministic, auditable decisions
  • You’re building at 100M+ entity scale
  • You need 1000× cost reduction
  • You need multi-signature consensus for AI actions
  • You need instant deployment (no learning period)

Technical Differentiators

1. Hyperbolic Geometry for Trust

d_H(x, y) = (2/√c) · arctanh(√c · ||(-x) ⊕_c y||)
  • Trust lives in curved space (Poincaré ball)
  • Distance from “center of trust” determines risk
  • Mathematically provable thresholds

2. Harmonic Scaling Law

H(d, R) = φ^d / (1 + e^(-R))
  • Golden ratio (φ = 1.618) scaling
  • Exponential cost as distance increases
  • Reputation-dampened response

3. Sacred Tongue Encoding

  • 6 cryptolinguistic tongues
  • 256 tokens per tongue (16×16 grid)
  • Human-readable audit trails
  • Spectral fingerprint per tongue

4. Roundtable Consensus

Action Required Tongues Policy
read KO Standard
write KO Standard
deploy KO + RU Strict
delete KO + RU Strict
admin RU + UM + DR Critical
security RU + UM + DR Critical

5. Post-Quantum Ready

  • ML-KEM-768 (key encapsulation)
  • ML-DSA-65 (digital signatures)
  • Hybrid mode (classical + PQC)
  • 128-bit quantum security

Bottom Line

  Darktrace SCBE-AETHERMOORE
Best for Traditional IT monitoring AI/Agent governance
Approach Smart camera (learns & alerts) Mathematical walls (prevent)
Maturity 10+ years production Pilot-ready
Cost \(\) $
Quantum-safe Partial Full
AI-specific Generic Specialized

Darktrace: King of AI-driven detection

SCBE-AETHERMOORE: King of mathematical prevention


Call to Action

SCBE-AETHERMOORE is pilot-ready with specialized AI agent governance that Darktrace doesn’t offer.

Contact: sales@scbe-aethermoore.com Demo: https://scbe-aethermoore.com/demo Documentation: See FULL_SYSTEM_ENABLEMENT.md


Last updated: January 2026


© 2026 Aethermoore - Issac Davis, Founder | Patent Pending (63/961,403) | Products | Demo

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