Cyber Circuit - GPU-Accelerated Cybersecurity Intelligence

GPU-Accelerated Cybersecurity Intelligence

Agentic AI for evidence-based cyber defense, with a quantum-classical research layer

Cyber-Circuit is a GPU-accelerated cybersecurity intelligence platform for anomaly detection, threat triage, and evidence-based response. It combines autoencoder-trained machine-learning models, agentic AI workflows, and IBM Quantum data telemetry research pipelines โ€” benchmarking emerging signals against strong classical baselines rather than assuming quantum advantage. Powered by QLLMeโ„ข (Quantum-classical Learning & ML engine), our research-grade analysis platform.

๐Ÿง 
Autoencoder Anomaly Detection
A trained 7.89M-parameter autoencoder scores telemetry for anomalous patterns
๐Ÿค–
Agentic Triage Workflows
Strategic AI agents prioritize, correlate, and explain security-relevant events
โš›๏ธ
Quantum-Classical Research
IBM Quantum telemetry treated as an experimental signal, measured before it is claimed

๐Ÿ“ง Contact Us

info@quantum-clarity.com

Email us for live demos, pricing information, evaluation pilots, or research inquiries.

Please include your name, company, role, and number of endpoints in your message.

BUILT FOR SECURITY TEAMS IN REGULATED, HIGH-STAKES ENVIRONMENTS

๐Ÿฆ Financial Services ๐Ÿฅ Healthcare ๐Ÿ›๏ธ Government โšก Energy & Utilities

The Enterprise Security Challenge

โŒ Traditional Security Falls Short

  • Alert Fatigue: SOC teams drowning in 10,000+ daily alerts with high false-positive rates
  • APT Blind Spots: Nation-state actors and sophisticated malware evade signature-based detection
  • Slow Response: Breaches frequently take months to detect and weeks to contain
  • Compliance Burden: Manual evidence collection is costly and slow
  • Skills Gap: Millions of cybersecurity positions remain unfilled globally
  • Rising Costs: Cyber insurance premiums climb while coverage shrinks

โœ“ The Cyber-Circuit Approach

  • Autoencoder Anomaly Scoring: A trained 7.89M-parameter model flags unusual patterns in telemetry
  • Agentic Triage: Strategic AI agents prioritize, correlate, and explain alerts to reduce noise
  • Evidence-Based Response: Automated, auditable workflows for faster, defensible decisions
  • Automated Compliance: SOC 2, ISO 27001, HIPAA, PCI-DSS evidence collection and reporting
  • Force Multiplier: Helps small teams cover large endpoint estates
  • Quantum-Classical Research: IBM Quantum-derived features are benchmarked, not assumed, against classical baselines

A Platform That Tests Its Own Claims

Most quantum-security marketing is hand-wavy. Cyber-Circuit is built to validate, not assert.

๐Ÿ”ฌ
Audit-Grade Methodology
Reproducible feature extraction and benchmarking, designed so results can be independently checked
๐Ÿ“Š
Classical Baselines First
Quantum-derived features must beat strong classical models before any claim is made
โšก
GPU-Accelerated Pipelines
NVIDIA RTX acceleration for training, inference, and large-scale telemetry analysis
๐Ÿค–
Agentic SOC Triage
AI agents correlate and explain events to cut alert noise and speed analyst decisions
๐Ÿ“‹
Compliance Automation
Evidence collection and reporting mapped to major regulatory frameworks
โš›๏ธ
1,500+ IBM Quantum Jobs
A real IBM Quantum data telemetry corpus powers the autoencoder-trained models and research layer

Where Cyber-Circuit Fits in Your Stack

Designed to augment existing SIEM and XDR investments โ€” not rip and replace them

Capability What Cyber-Circuit Provides
Autoencoder-Based Anomaly Detection Trained 7.89M-parameter model scores telemetry for unusual patterns
Agentic AI Triage Strategic agents prioritize, correlate, and explain alerts
GPU Acceleration NVIDIA RTX-optimized training and inference pipelines
Multi-Vendor SIEM/XDR Integration Connectors for CrowdStrike, Splunk, Cisco XDR, Cortex XDR, Okta, Sentinel
Automated Compliance Reporting SOC 2, ISO 27001, NIST 800-53, HIPAA, PCI-DSS, GDPR evidence and reports
Post-Quantum Cryptography Assessment Scans for crypto weaknesses and tracks migration readiness
Natural Language Security Copilot Plain-English querying of incidents and security posture
Quantum-Classical Research Layer IBM Quantum-derived features benchmarked against classical baselines

๐Ÿ–ฅ๏ธ Operational Dashboards

Command centers for security operations visibility

๐ŸŽ›๏ธ
Security Command Center
Unified glass-pane view of your security infrastructure with live threat feeds and analytics
๐Ÿค–
SRM Dashboard
Security Reasoning Model with multiple analysis modes: tactical, strategic, quantum (QAOA/VQE research), and hybrid
๐Ÿ’ฌ
Security Copilot
Natural language interface: "Show me privilege escalation attempts" โ€” instant correlated answers
๐Ÿ›ก๏ธ
Ransomware Shield
Rapid anomaly detection with point-in-time restoration and automated containment workflows
๐ŸŽฏ
Insider Threat Analytics
Behavioral analytics (UEBA) to surface anomalous account and user activity
๐Ÿง 
AI Attack Detection
Behavioral analysis engine to help counter AI-generated phishing, deepfakes, and synthetic media
โš›๏ธ
Quantum Research Console
Live benchmarking of quantum-derived features against classical baselines, with reproducible metrics
๐Ÿ“‹
Compliance Central
SOC 2, ISO 27001, NIST, HIPAA, PCI-DSS, GDPR โ€” audit reports with evidence collection

Pre-Built Enterprise Integrations

Bi-directional SIEM adapters for your existing security infrastructure

๐Ÿฆ… CrowdStrike Falcon
๐Ÿ” Okta Identity
๐Ÿ“Š Splunk Enterprise
๐Ÿ”ท Cisco XDR
๐ŸŸง Palo Alto Cortex
โ˜๏ธ Azure Sentinel

โœ“ No rip-and-replace required โ€ข โœ“ Augments existing investments โ€ข โœ“ Deploy without lengthy migrations

Start with an Evaluation Pilot

See how Cyber-Circuit surfaces anomalies and supports triage against your own telemetry

Engagements are scoped to your environment โ€” endpoint count, integrations, and deployment model (cloud, hybrid, or on-premise). We start with a focused pilot on a sample of your telemetry, then size a plan around what the data shows.

Pilots can include autoencoder-based anomaly scoring, agentic triage, multi-vendor XDR integration, and automated compliance reporting.

Contact: info@quantum-clarity.com

Email us to scope a pilot, demo, or evaluation

๐ŸŒŒ Real IBM Quantum Data Integration

Research-grade IBM Quantum data telemetry โ€” captured from authentic IBM quantum hardware and used to train our autoencoder models

โš›๏ธ
IBM Torino Integration
Drawing on 1,500+ IBM Quantum jobs and over 1,000,000 measured quantum states captured from IBM Torino's 133-qubit processor, this IBM Quantum data telemetry forms a high-dimensional feature space used to train our autoencoder models and run benchmarking experiments.
๐Ÿ”ฌ
Quantum Circuit Categories
Bell states, GHZ states, random circuits, and Hadamard gates with entropy metrics ranging 0.79โ€“3.65 bits, captured with measured entanglement fidelity for reproducible analysis.
๐Ÿ“Š
SQL Live Telemetry Feed
A SQL-backed telemetry pipeline supports drift monitoring and auditable, reproducible model decisions, so every experiment can be traced back to its source data.
Powered by QLLMeโ„ข โ€” Quantum-Classical Research Engine

๐Ÿ”ญ Quantum-Classical Research Layer

IBM Quantum telemetry meets rigorous benchmarking against classical baselines

๐ŸŒ
Feature Extraction
Reproducible quantum-result features โ€” output entropy, bitstring concentration, divergence from simulator baselines โ€” extracted from 1,024,000 measurement states for controlled experiments.
๐ŸŽฏ
Benchmark Harness
Quantum-derived features are tested alongside classical models, with ablations using shuffled and synthetic features to verify that any signal is real and not an artifact.
๐Ÿ”
Honest Reporting
We report where quantum-derived features do โ€” and do not โ€” add measurable value over strong classical baselines, so claims stay grounded in evidence.

Why It Matters

The same IBM QPU-trained autoencoder (7.89M parameters) that powers the training console feeds the platform's anomaly scoring. Rather than assuming quantum advantage, Cyber-Circuit measures it โ€” which is exactly what makes the research defensible.

๐Ÿค– Strategic Agent System

Autonomous AI-driven triage and decision support

๐ŸŽฏ
Autonomous Decision Making
AI-powered strategic agent with confidence-based threat assessment (0-100% scoring). Real-time decision history tracking with impact scoring and adaptive learning from threat patterns.
โšก
Strategic Response Framework
Intelligent threat prioritization, dynamic resource allocation, automated escalation management, and pattern recognition for predictive defense capabilities.
๐Ÿ”ฎ
Quantum-Inspired Reasoning
Quantum-inspired algorithms for multi-dimensional threat assessment, evaluated as part of the broader research pipeline rather than presented as proven advantage.
0-100%
Confidence Scoring
Adaptive
Pattern Learning
Auditable
Decision History
24/7
Autonomous Operation

๐ŸŽฏ MCP Orchestration Engine

Model Context Protocol orchestration that coordinates CUDA, cuDNN, and PyTorch for quantum-classical workflow acceleration

โšก
Persistent Context
GPU memory stays "warm" between operations, eliminating initialization overhead and reducing latency compared to cold-start approaches.
๐Ÿ”ง
Multi-Framework Coordination
Simultaneous orchestration of CUDA, cuDNN, PyTorch, and TensorFlow Quantum with shared context across frameworks.
๐Ÿš€
Quantum-Classical Pipeline
Smooth transitions between quantum pattern analysis and classical verification without GPU context loss or framework switching overhead.
MCP-Powered Architecture

๐ŸŒ Multi-Vendor XDR Integration

Unified threat correlation across Cisco XDR and Palo Alto Cortex XDR with a single pane of glass

๐Ÿ”ท
Cisco XDR Connector
Native integration with Cisco SecureX/XDR surfaces alerts, incidents, and telemetry directly into Cyber-Circuit, linking network, endpoint, and identity signals into cohesive attack stories.
๐ŸŸง
Palo Alto Cortex XDR
Bi-directional enrichment with Cortex XDR: alerts are re-scored using GPU-accelerated correlation and IBM quantum hardware research data (Brisbane, Torino, Kyiv), then pushed back as comments, tags, and updated priorities.
๐ŸŽฏ
Unified XDR Hub
A single operational console for SOC teams: auto-refresh dashboards, cross-vendor incident timelines, and unified case views so analysts never have to jump between tools to understand an attack chain.

Quantum-Classical Correlation

Cyber-Circuit experiments with encoding alert correlations as quantum features and benchmarking them against classical correlation, with the goal of reducing noise in busy SOC environments where it demonstrably helps.

๐Ÿ–ฅ๏ธ SIEM Operations Center

Comprehensive security information and event management with compliance insights

๐Ÿ“Š
Log Aggregation & Correlation
Advanced correlation engine processes security events from multiple sources, identifying patterns and relationships that indicate potential threats or policy violations.
๐Ÿšจ
Alert Management System
Centralized alert tracking with acknowledgment workflows, assignment capabilities, and escalation automation. Full audit trail for compliance and incident response.
๐Ÿ“‹
Compliance Reporting
Pre-built and customizable compliance reports for GDPR, HIPAA, PCI-DSS, SOC 2, and other regulatory frameworks. Automated scheduling and distribution.

๐Ÿงพ Automated Compliance Dashboard

SOC 2, ISO 27001, NIST 800-53, HIPAA, PCI-DSS, and GDPR mapped directly to live telemetry and evidence

Framework Coverage Evidence Collection Gap Analysis Audit-Ready Reports

๐ŸŽ›๏ธ Integrated Dashboards & Command Centers

Operational consoles for security visibility and control

๐Ÿค–
Security Reasoning Model (SRM)
An AI system designed for cybersecurity operations. Unlike general-purpose AI models, SRM is oriented toward threat analysis, strategic defense planning, and security decision support. Features tactical, strategic, quantum-research, and hybrid reasoning modes.
4 Reasoning Modes Decision Support
๐Ÿง 
AI Attack Detection (Q-BAE)
The Behavioral Analysis Engine (Q-BAE) is designed to help counter AI-generated phishing and deepfake social engineering. It analyzes synthetic media indicators, AI-generated text patterns, and automated attack frameworks.
Deepfake Detection AI Phishing Defense
๐ŸŽฏ
Insider Threat Detection
Behavioral analysis (UEBA) that surfaces anomalous activity from accounts and users. Quantum-derived features are evaluated as candidate signals within the research pipeline, benchmarked against classical behavioral models.
UEBA Anomaly Scoring
๐Ÿ›ก๏ธ
Ransomware Defense Shield
Anomaly detector with automated containment and rapid rollback. Scoring highlights suspicious encryption bursts, with point-in-time restoration, automated process freezing, and emergency snapshots.
Rapid Detection Auto-Containment Point-in-Time Recovery
๐Ÿ’ฌ
Security Copilot (Natural Language for SOC)
Natural language interface for security analysts. Ask questions in plain English and get answers about threats, incidents, and security posture. "Show me all lateral movement attempts in the last 24 hours" returns correlated analysis.
Natural Language Instant Answers
โš›๏ธ
Quantum Research Dashboard
Live visualization of the quantum-classical benchmarking pipeline: feature distributions, entanglement fidelity, and head-to-head metrics comparing quantum-derived features against classical baselines.
Benchmarking Live Metrics
๐Ÿ“‹
Compliance Dashboard
SOC 2, ISO 27001, NIST 800-53, HIPAA, PCI-DSS, GDPR โ€” automated compliance monitoring and audit-ready reporting. Evidence collection, gap analysis, and one-click report generation.
6 Frameworks Auto-Evidence Audit-Ready
๐ŸŽ›๏ธ
Security Command Center
Unified operational console for security teams. Real-time threat feeds, incident timelines, circuit visualization, GPU performance monitoring, and interactive system controls. Single pane of glass for security operations.
Unified Console Real-Time

๐Ÿ”— Enterprise XDR Integrations with SIEM Adapters

Pre-built connectors with bi-directional SIEM adapters for seamless enterprise integration

๐Ÿฆ…
CrowdStrike Falcon
EDR/XDR Integration
SIEM Adapter
๐Ÿ”
Okta Identity Cloud
IAM Integration
SIEM Adapter
๐Ÿ“Š
Splunk Enterprise
SIEM Integration
SIEM Adapter
๐Ÿ”ท
Cisco XDR
Network Security
Native Integration
๐ŸŸง
Palo Alto Cortex XDR
Extended Detection
Bi-Directional
โ˜๏ธ
Azure Sentinel
Cloud-Native SIEM
Native Integration

Why SIEM Adapters Matter: Bi-directional data flow means Cyber-Circuit enriches your existing tools with ML-driven analysis while ingesting their telemetry for unified threat correlation.

โœ“ No rip-and-replace โ€ข โœ“ Augments existing investments โ€ข โœ“ Unified threat visibility โ€ข โœ“ ML-enhanced correlation

๐Ÿ›ก๏ธ Core Cybersecurity Features

Protection powered by GPU-accelerated machine learning and agentic AI

โš›๏ธ
Quantum-Classical Detection Research
Quantum circuits built with TensorFlow Quantum and Cirq using real IBM quantum data. The platform analyzes whether quantum-derived telemetry features add measurable signal to threat detection over classical baselines.
๐Ÿš€
GPU-Accelerated Performance
Optimized for NVIDIA RTX hardware with CUDA 12.x support. MCP orchestration delivers acceleration with persistent GPU context and zero framework switching overhead.
๐Ÿง 
Advanced AI/ML Pipeline
CNN, GNN, LSTM, and RNN networks with PennyLane optimization and ensemble methods. Hybrid quantum-classical models are continuously trained and benchmarked for threat classification.
๐ŸŒ
Real-Time Network Monitoring
Advanced packet capture and deep packet inspection with multi-interface support. Protocol analysis for TCP/IP, HTTP/HTTPS, DNS with intelligent traffic filtering and behavioral analysis.
โšก
Automated Response System
Intelligent automated response engine with real-time threat containment. Dynamic firewall rules, network segmentation, and endpoint quarantine with configurable, auditable playbooks.
๐Ÿ”
Cryptographic Assessment
Post-quantum readiness assessment engine with crypto vulnerability detection. Scanning for encryption weaknesses, NIST migration tracking, and planning with cost estimation.
๐Ÿ“ง
Enterprise Email Alerting
Multi-channel alert management with SMTP integration, customizable templates, and role-based routing, with automated escalation workflows.
๐Ÿ“Š
System Performance Monitoring
Comprehensive resource and health monitoring with CPU, memory, GPU, and network I/O tracking, with predictive failure detection and automated recovery capabilities.
๐ŸŽ›๏ธ
Real-Time SOC Dashboard
Professional Security Operations Center interface with live threat feeds, circuit visualization, GPU performance monitoring, and interactive system controls for security teams.

๐Ÿ”ฌ Production-Ready Technology Stack

Built on proven quantum computing and machine learning frameworks with enterprise deployment capabilities

MACHINE LEARNING
7.89M-Parameter Autoencoder
QUANTUM COMPUTING
TensorFlow Quantum 0.7.2
QUANTUM COMPUTING
Cirq 1.3.0
QUANTUM COMPUTING
PennyLane 0.42.1
QUANTUM DATA
IBM Quantum (1,024,000 states)
QUANTUM DATA
32-D Latent Manifold
AI/ML STACK
TensorFlow 2.13.0
AI/ML STACK
CNN, GNN, LSTM, RNN
GPU ACCELERATION
NVIDIA RTX Hardware
GPU ACCELERATION
CUDA 12.x + Tensor Cores
ORCHESTRATION
MCP Multi-Framework
AI AGENT
Strategic Decision Making
MONITORING
Scapy Packet Capture
COMMUNICATION
SMTP/API/Mobile Push
CRYPTOGRAPHY
Post-Quantum Assessment
DATA
SQL Live Telemetry
SIEM
Compliance Reporting
DEPLOYMENT
Linux Systemd + Docker

๐Ÿ“Š Platform at a Glance

Verifiable facts about the data, models, and infrastructure behind Cyber-Circuit

1,500+
IBM Quantum Jobs Executed
1M+
Quantum Measurement States
7.89M
Autoencoder Parameters
32-D
Latent Feature Space
4
IBM Backends Used
6
Compliance Frameworks
RTX
NVIDIA GPU Accelerated
24/7
Autonomous Operation

Detection and response performance figures are established per-deployment during evaluation pilots against your own telemetry, rather than quoted as universal benchmarks.

๐ŸŽฏ Deployment Scenarios

๐Ÿข Enterprise Security Operations Centers

24/7 threat monitoring with MCP-accelerated pattern recognition. Automated response workflows with email notifications and real-time dashboard integration.

SOC Integration Auto-Response

๐Ÿญ Critical Infrastructure Protection

Specialized detection for SCADA and industrial control systems. Advanced persistent threat detection with correlation analysis and automated quarantine.

SCADA Ready APT Detection

๐Ÿฆ Financial Services Security

Real-time fraud detection with ML-driven pattern recognition. Cryptographic assessment for post-quantum readiness and regulatory compliance tracking.

Fraud Detection Compliance

โ˜๏ธ Cloud & Hybrid Environments

Multi-cloud security with ML-driven anomaly detection. Container protection with GPU-accelerated behavioral analysis and automated response.

Multi-Cloud Containers

๐Ÿฅ Healthcare Data Protection

HIPAA-aligned threat detection with privacy-focused monitoring. Real-time monitoring of patient data access with automated compliance reporting.

HIPAA Privacy

๐Ÿ›๏ธ Government & Defense

Advanced threat detection for sensitive networks. Post-quantum cryptography readiness assessment with auditable security protocols and real-time intelligence.

Sensitive Networks Defense Grade

๐Ÿ”ฌ Research & Development

A platform for cybersecurity and quantum-classical research. Modular architecture enables experimentation with quantum machine learning and real-world threat data.

Research Ready Modular

โšก Energy & Utilities

Protection for smart grids and energy infrastructure. Real-time anomaly detection for power distribution systems with automated threat response.

Smart Grid Real-time

Ready to Evaluate Cyber-Circuit?

See how GPU-accelerated ML, agentic AI, and a quantum-classical research layer can support your security operations

Schedule a live demo to see how Cyber-Circuit's IBM Quantum-trained autoencoder (7.89M parameters, 1,024,000 quantum states), autonomous strategic AI agents, and comprehensive SIEM operations work together โ€” and how we benchmark quantum-derived features against classical baselines so claims stay grounded in evidence.

Contact: info@quantum-clarity.com

Email us for pricing, demos, or evaluations

Contact: info@quantum-clarity.com

Email us for pricing, demos, or evaluations

Platform Highlights:

โš›๏ธ 1,500+ IBM Quantum Jobs โ€ข ๐Ÿง  Autoencoder-Trained Models (7.89M Parameters) โ€ข ๐Ÿ”ญ Quantum-Classical Research Layer

๐Ÿค– Strategic AI Agent โ€ข ๐Ÿ“ง Multi-Channel Alerts โ€ข ๐Ÿ–ฅ๏ธ Enterprise SIEM โ€ข ๐Ÿš€ Real-Time Response

โšก Linux Deployment Ready โ€ข ๐ŸŽฎ NVIDIA RTX Optimized โ€ข ๐Ÿข Enterprise Support Available