Automates incident response, playbooks, and enterprise workflows.
Analyzes logs, emails, and user behavior to uncover threats.
Safeguards research, designs, and sensitive data across all devices.
One of the world's leading AI researchers behind the technology. Enterprise cybersecurity experts who has sold to Fortune 100 companies. Together, their work spans since 2006, grounded in published, peer-reviewed AI research.
It runs on predictive, error-compensating neural networks that forecast their own errors and correct them in real time.
The method is independently validated in peer-reviewed literature, including IEEE Access work on error-compensated wavelet neural networks.1 It is the foundation of CYBERDROID Neural Detection.
Each family targets a different class of adversary behavior, fusing into coherent attack-chain narratives with no single-method blind spots.
Five more proprietary families are available under NDA, covering identity drift, kernel-level egress, and cross-product attack-chain reconstruction.
Cortical coding and the 180+ algorithm portfolio aren't lab curiosities. Two surfaces put them in front of SOC teams daily.
Cortical coding in production. CYBERDROID fuses 11 telemetry classes across all 15 algorithm families into one actor-centric reasoning graph.
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Where detection meets the operator. Every event arrives as a structured investigation: actor context, evidence chains, recommended actions, not a queue line.

Not assembled from acquired startups. One continuous research program, led by the same people who designed it.
A five-year program in predictive error-compensated architectures, the foundation under CYBERDROID Neural Detection. Full bibliography under NDA.
High-Performance Time Series Prediction With Predictive Error Compensated Wavelet Neural Networks.
Ustundag, B. B., & Kulaglic, A.
IEEE Access, 8, 210532–210541.
Stock Price Prediction Using Predictive Error Compensation Wavelet Neural Networks.
Kulaglic, A., & Ustundag, B. B.
Computers, Materials & Continua, 68(3), 3577–3593. 33% RMSE improvement over LSTM.
Predictive Error Compensating Wavelet Neural Network Model for Multivariable Time Series Prediction.
Kulaglic, A., & Ustundag, B. B.
TEM Journal, 10(4), 1955–1963. Extends PEC-WNN to multivariable input.
Improvement in Prediction Performance Using Predictive Error Compensated Neural Networks.
Kulaglic, A., & Ustundag, B. B.
Springer Lecture Notes in Networks and Systems. Ongoing program investment through 2024.
A 60-minute session with the engineers who built it: architecture, the algorithm portfolio, a live investigation on your own telemetry, and the full bibliography under NDA.
Under mutual NDA · Engineer-led session · No sales overlay
