The xAQUA Risk Intelligence Engine combines ARIMA time-series modeling with LSTM neural networks to forecast your composite risk score 14 days forward — with confidence bands. Drift is detected before it becomes a breach. Correlations are surfaced no single tool can see.
AutoRegressive Integrated Moving Average models capture the linear trend and seasonality in your risk score history — detecting cyclical compliance patterns and long-term drift vectors.
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LSTM Neural Network
Long Short-Term Memory networks learn non-linear patterns across your multi-source signal stream — capturing event sequences and tool-specific behaviors that ARIMA alone cannot model.
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σ-Band Confidence
Forecast output includes 1σ and 2σ confidence bands so you know how certain the prediction is. Walk into board meetings with a range, not just a number. Uncertainty is information too.
Drift detection continuously monitors your security posture across all connected sources. When your score degrades outside normal variance, action cards are generated and prioritized automatically — in under 60 seconds.
Live Drift Event — Example
• Drift Detected — Feb 10, 14:23 UTC
Score drop
81 → 70 (−11 pts)
Primary source
AWS Security Hub
Correlated source
MS Sentinel (+72h)
Action cards
4 generated
Time to detect
<47 seconds
Cross-Source Correlation
The Pattern No Single Tool Sees
Sentinel logged 3 failed MFA attempts on Feb 8. AWS logged 2 unusual IAM API calls on Feb 9. SecureScore dropped 11 points on Feb 10.
Correlation Confidence
0%
"Aegis correlated an alert cluster from 72 hours prior to a SecureScore drop. No human analyst would have caught that connection across three tools."
The RIE runs 10 continuous intelligence jobs against your unified signal stream. ETL populates raw tables. RIE produces the intelligence — action cards, drift alerts, correlation findings, predictions — that your team actually acts on.
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KRI Computation
32 key risk indicators computed continuously across all sources
Prioritized, AI-authored remediation steps — <60s from signal
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Anomaly Detection
Behavioral baseline monitoring — detects outliers before they escalate
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Evidence Tagging & Lineage
Hash-verified, time-stamped evidence chain from raw signal to audit artifact
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Drift Detection
Posture degradation flagged before breach — σ-band thresholds
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Cross-Source Correlation
Multi-signal event correlation across all 42+ connected sources
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Compliance Posture Scoring
Real-time pass/fail mapping across all active frameworks
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Narratix Report Generation
AI-authored board and compliance reports from live data
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AI Governance Monitoring
Continuous NIST AI RMF, ISO 42001, OWASP LLM Top 10 posture tracking
See the Forecast
Against Your Own Data.
No other GRC platform forecasts your risk score 14 days forward. See what's coming before it arrives — in a live demo against your environment or our LCI reference dataset.
