SCBE-AETHERMOORE: Competitive Analysis 2026
Document: COMPETITIVE-2026-001 Date: January 2026 Purpose: Market positioning and competitive differentiation
Executive Summary
The AI security market is at an inflection point. With Gartner predicting 40% of enterprise applications will embed AI agents by end of 2026 (up from 5% in 2025), and only 6% of organizations having advanced AI security strategies, there’s a massive governance gap.
SCBE-AETHERMOORE’s Opportunity: Purpose-built AI agent governance with quantum-safe cryptography fills a gap no major vendor fully addresses.
1. Competitor Analysis
1.1 Darktrace
Company Profile:
- Founded: 2013, Cambridge UK
- Employees: 2,400+
- Customers: ~10,000
- Patents: 200+ applications
- Public: Listed on LSE
What They Offer:
| Product | Function |
|---|---|
| Darktrace / NETWORK | Network traffic anomaly detection |
| Darktrace / EMAIL | Email security beyond inbox |
| Darktrace / CLOUD | Multi-cloud security |
| Darktrace / ENDPOINT | EDR complement |
| Darktrace / OT | Operational technology security |
| Cyber AI Analyst | Automated incident investigation |
How They Offer It:
- Self-Learning AI: Learns “normal” behavior patterns for each organization
- Anomaly Detection: Identifies deviations from baseline
- Autonomous Response: Can take action to contain threats
- SaaS + On-Prem: Flexible deployment
UI/UX - Threat Visualizer:
- 3D interactive visualization of network topology
- Color-coded alerts (severity-based)
- Real-time anomaly highlighting
- Playback capability for forensic analysis
- Dynamic situational dashboard
- Mobile app available
Pricing:
- Custom quotes based on organization size
- Reported as “upper price segment”
- Add-ons increase costs significantly
- Typical enterprise: $100K-500K+/year
Strengths:
- Mature product (10+ years)
- Strong brand recognition
- Comprehensive coverage (network, email, cloud, OT)
- Self-learning reduces configuration
Weaknesses:
- Detective, not preventive (finds threats after they occur)
- Black-box ML decisions (not explainable)
- Not purpose-built for AI agents
- No quantum-safe cryptography
- High cost for SMBs
1.2 CrowdStrike
Company Profile:
- Founded: 2011
- Market Cap: ~$80B
- Customers: 29,000+
- Platform: Falcon
What They Offer:
| Product | Function |
|---|---|
| Falcon Prevent | Next-gen antivirus |
| Falcon Insight | EDR |
| Falcon OverWatch | Managed threat hunting |
| Falcon Identity | Identity protection |
| Falcon Cloud | Cloud workload protection |
| Falcon AIDR (NEW 2025) | AI Detection & Response |
| Charlotte AI | AI-powered assistant |
Falcon AIDR (December 2025 Launch):
- First unified platform for enterprise AI security
- Secures: data, models, agents, identities, infrastructure, interactions
- Blocks prompt injection (180+ techniques catalogued)
- Stops risky AI use in real-time
- Protects sensitive data from reaching models
How They Offer It:
- Lightweight agent deployment
- Cloud-native architecture
- Single console for all modules
- Threat intelligence integration
- API-first design
UI/UX:
- Unified dashboard for all Falcon modules
- Charlotte AI AgentWorks: No-code agent builder
- Natural language security workflows
- Enterprise Graph visualization
- Real-time alert triage
Pricing:
- Falcon Go: ~$60/device/year (basic)
- Falcon Pro: ~$100/device/year
- Falcon Enterprise: ~$185/device/year
- Falcon Elite: Custom pricing
Strengths:
- Market leader in EDR
- Falcon AIDR directly addresses AI agent security
- Strong threat intelligence
- Charlotte AI for automation
- SGNL acquisition (Jan 2026) for identity
Weaknesses:
- Agent-based (requires deployment)
- Focused on detection/response, not prevention
- No quantum-safe cryptography
- AIDR is new (limited track record)
- Complex pricing for full stack
1.3 Post-Quantum Cryptography Vendors
Market Size: $0.42B (2025) → $2.84B (2030), 46.2% CAGR
Major Players:
| Vendor | Focus | Strength |
|---|---|---|
| NXP | Hardware encryption | Broad portfolio, enterprise presence |
| Thales | HSMs, key management | Luna HSMs with PQC |
| AWS | Cloud PQC toolkit | Scale, integration |
| Palo Alto Networks | Network security | Firewall integration |
| IBM | Quantum-safe service | Mainframe focus |
| PQShield | Crypto IP | NIST table seat, OEM-friendly |
| ISARA | PKI transition | Hybrid toolkits |
| Crypto4A | HSMs | Government/defense |
What They Offer:
- NIST-certified PQC algorithms (ML-KEM, ML-DSA, SLH-DSA)
- Hardware Security Modules (HSMs)
- Crypto-agility frameworks
- Migration tools for existing PKI
How They Offer It:
- Mostly infrastructure-level (not application-layer)
- HSM appliances or cloud services
- SDK/libraries for developers
- Consulting for migration
Weaknesses:
- Infrastructure-focused, not AI governance
- No real-time decision engine
- Complex integration
- Expensive HSMs ($50K-200K+)
1.4 Emerging AI Security Platforms
Gartner’s AI Security Platforms (AISP) Trend:
- Predicted: 50%+ enterprises using AISPs by 2028 (from <10% today)
- Focus: AI-native security risks
Notable Players:
| Vendor | Focus |
|---|---|
| Robust Intelligence | AI model security |
| Protect AI | ML pipeline security |
| HiddenLayer | Adversarial ML defense |
| CalypsoAI | LLM security |
| Lakera | Prompt injection defense |
Gap: Most focus on model security, not agent governance.
2. Market Demand: What Enterprises Want in 2026
CISO Top Priorities (Source: CSO Online, SecurityWeek)
| Priority | % Citing | SCBE Capability |
|---|---|---|
| AI Governance | #1 | 14-layer governance pipeline |
| Zero Trust | #2 | Every action requires fresh token |
| Identity (Human + Machine) | #3 | Agent identity + trust scoring |
| Attack Surface Visibility | 40% | Real-time agent monitoring |
| Explainable Decisions | Growing | Full score breakdown |
| Quantum-Safe | Emerging | ML-KEM-768, ML-DSA-65 |
Key Market Insights
AI Agent Security Gap:
- 40% of enterprise apps will embed AI agents by end of 2026
- Only 6% have advanced AI security strategy
- 75% of leaders prioritize security/compliance/auditability for agents
- 50% of executives plan $10-50M investment in agentic security
Zero Trust Shift:
- Moving from “ambition to necessity” in 2026
- Tactical, layer-by-layer implementation preferred
- Identity as the dominant control strategy
Governance as Enabler:
- Shift from “compliance overhead” to “competitive advantage”
- 60% restrict agent access to sensitive data without human oversight
- Human-in-the-loop required for high-risk workflows
Regulatory Pressure:
- ISO 42001, NIST AI RMF, GDPR mandate autonomous system controls
- Executive liability for AI failures becoming legal precedent
- Migration deadlines: 2030-2035 for quantum-safe
3. Competitive Positioning Matrix
Feature Comparison
| Capability | Darktrace | CrowdStrike | PQC Vendors | SCBE-AETHERMOORE |
|---|---|---|---|---|
| AI Agent Governance | Partial | AIDR (new) | No | Purpose-built |
| Approach | Detective | Detective | Infrastructure | Preventive |
| Explainable Decisions | No (black-box) | Partial | N/A | Yes (full) |
| Quantum-Safe Crypto | No | No | Yes | Yes |
| Real-time Authorization | No | AIDR | No | Yes (<5ms) |
| Fail-to-Noise | No | No | No | Yes |
| Consensus Mechanism | No | No | No | Yes (BFT) |
| Trust Scoring | Anomaly-based | Threat-based | N/A | Math-based |
| Audit Trail | Logs | Logs | HSM logs | Cryptographic proof |
| On-Prem Option | Yes | Yes | Yes | Yes |
| Price Point | \(\) | $$$ | \(\) | $$ |
Positioning Statement
SCBE-AETHERMOORE: The only solution combining AI agent governance + post-quantum cryptography + explainable, mathematically-proven decisions.
4. UI/UX Comparison
Darktrace Threat Visualizer
┌─────────────────────────────────────────────┐
│ 3D Network Topology │
│ ┌─────────────────────────────────────┐ │
│ │ ●───●───● [Anomaly Detected] │ │
│ │ /│\ │ \● │ │
│ │ ● ● ● ● ● │ │
│ │ │ │ │ │
│ │ ●────────● │ │
│ └─────────────────────────────────────┘ │
│ Alerts: 🔴 Critical 🟡 Warning 🟢 Normal │
│ [Investigate] [Playback] [Report] │
└─────────────────────────────────────────────┘
- Visually impressive but complex
- Requires training to interpret
- Focus on network topology
CrowdStrike Falcon
┌─────────────────────────────────────────────┐
│ Falcon Dashboard │
│ ┌──────────┬──────────┬──────────────────┐ │
│ │ Detects │ Incidents│ Threat Intel │ │
│ │ 142 │ 8 │ ADVERSARY: APT │ │
│ └──────────┴──────────┴──────────────────┘ │
│ Recent Alerts │
│ ├─ 🔴 Malware detected: endpoint-42 │
│ ├─ 🟡 Suspicious login: user@corp.com │
│ └─ 🟢 Policy updated: firewall-rule-17 │
│ [Investigate] [Contain] [Remediate] │
└─────────────────────────────────────────────┘
- Unified console
- Alert-centric workflow
- Endpoint-focused
SCBE-AETHERMOORE (Proposed)
┌─────────────────────────────────────────────┐
│ SCBE Agent Governance Dashboard │
│ ┌──────────┬──────────┬──────────────────┐ │
│ │ ✅ ALLOW │ ⏸️ QUEUE │ ❌ DENY │ │
│ │ 1,247 │ 23 │ 156 │ │
│ └──────────┴──────────┴──────────────────┘ │
│ │
│ Agent: fraud-detector-001 Trust: 0.92 │
│ Action: READ → transaction_stream │
│ ├─ L5-7: Distance 0.251 (safe zone) │
│ ├─ L12: H(d=1) = 2, risk: 0.03 │
│ └─ L13: Score 0.680 → ✅ ALLOW │
│ │
│ [View Details] [Override] [Audit Log] │
└─────────────────────────────────────────────┘
- Decision-centric (not alert-centric)
- Full explainability visible
- Simple, actionable interface
5. Gap Analysis: Where SCBE Wins
Unique Differentiators
| Gap in Market | SCBE Solution |
|---|---|
| Prevention vs Detection | 14-layer check BEFORE action executes |
| Explainability | Every score component visible and auditable |
| Quantum-Safe + Governance | Only solution combining both |
| Mathematical Proofs | Patent-backed theorems, not heuristics |
| Agent-Native | Built for AI-to-AI, not retrofitted |
| Fail-to-Noise | DENY returns nothing useful to attacker |
Competitive Moat
- Patent Protection: USPTO #63/961,403 covers 14-layer pipeline
- Mathematical Foundation: Hyperbolic geometry, not just ML
- First-Mover in Intersection: AI governance + PQC + explainability
- Cost Structure: Software-only, no HSM required for basic deployment
6. What Enterprises Want vs What SCBE Offers
| Enterprise Need | What They Ask For | SCBE Delivers |
|---|---|---|
| “Govern our AI agents” | Policy enforcement | 14-layer governance |
| “Zero trust for machines” | Continuous verification | Fresh token per action |
| “Explain why it blocked” | Audit trail | Full score breakdown |
| “Prepare for quantum” | PQC migration | ML-KEM-768, ML-DSA-65 |
| “Don’t leak info to attackers” | Secure denial | Fail-to-noise |
| “Fast decisions” | Low latency | <5ms p99 |
| “Work with our stack” | Integration | OIDC, Kafka, SIEM adapters |
| “Reasonable cost” | TCO management | Software license model |
7. Recommended Actions
Immediate (This Week)
- Update README with competitive positioning table
- Add UI mockups to docs showing dashboard concept
- Record demo video highlighting explainability
Short-Term (This Month)
- Build basic dashboard (React + WebSocket from existing code)
- Create one-pager comparing SCBE to Darktrace/CrowdStrike
- Target outreach to CISOs via LinkedIn
Medium-Term (Q1 2026)
- API wrapper with 6 core endpoints
- SIEM integration (Splunk, QRadar)
- Compliance mapping (SOC 2, ISO 42001)
Positioning Message
For AI-First Enterprises:
“While Darktrace tells you something went wrong, and CrowdStrike helps you respond, SCBE-AETHERMOORE prevents unauthorized AI agent actions before they happen — with quantum-safe cryptography and decisions you can explain to auditors.”
For Security Teams:
“Your AI agents operate at machine speed. SCBE governs them with mathematical certainty, not probabilistic ML.”
For Executives:
“When regulators ask why your AI did something, SCBE gives you a cryptographic proof, not a log entry.”