The Missing Data Layer for Cybersecurity AI
The Cognitive Data Grid transforms fragmented security telemetry into structured, time-aware knowledge that AI systems, analytics tools, and security teams can actually use.
Security data is often stored, indexed, queried, and reported across SIEMs, data lakes, lakehouses, warehouses, databases, and cybersecurity platforms. These systems are valuable, but they were not designed to create reusable knowledge for AI-driven security workflows.
The Cognitive Data Layer adds the missing layer between security telemetry and security intelligence — organizing activity into contextual, behavioral, temporal, and relational knowledge structures that support analytics, anomaly detection, and agentic AI workflows.
What Is the Cognitive Data Grid?
The Cognitive Data Layer is the core of the Knowledge Grid platform. It converts security telemetry into reusable knowledge structures that preserve meaning, context, relationships, behavior, and time.
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Traditional data platforms help organizations collect and query data. The Cognitive Data Layer helps machines and analysts understand it.
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It does this by transforming security activity into structured representations that can be used repeatedly across security analytics, unsupervised anomaly detection, AI-assisted investigation, agentic SOC workflows, and cybersecurity platform enablement.
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The Cognitive Data Layer turns security telemetry into machine-usable knowledge.
Reusable Knowledge Structures for Security Intelligence
The Cognitive Data Layer creates reusable knowledge structures that capture security meaning in a form that analytics systems, anomaly models, AI workflows, and security applications can use.
Knowledge Descriptions
Compact representations of security activity across entities, events, attributes, and behaviors.
Feature Summaries
High-signal summaries of patterns, behaviors, frequencies, combinations, and changes over time.
Temporal Histograms
Time-aware representations that help identify distributions, baselines, deviations, and behavioral shifts.
Correlations
Relationships between users, devices, accounts, applications, destinations, events, and other security-relevant entities.
Semantic Enrichment
Added context that makes telemetry more meaningful for humans, analytics, and AI workflows.
How it works
Knowledge Structures Overview
Knowledge Grid organizes data through a set of purpose-built structures that capture what exists in the data, how elements relate, and what context gives them meaning. Together, they create an AI-ready representation optimized for search, detection, model development, and agentic workflows.
Built for AI-Ready Cybersecurity Use Cases
The Cognitive Data Layer provides the foundation for Knowledge Grid’s platform and cybersecurity use cases by making security data more structured, contextual, reusable, and AI-ready.
Unsupervised Anomaly Detection
Find unknown and emerging behavioral patterns that rules, signatures, and predefined detections may miss.
Agentic SOC Enablement
Give AI-driven SOC workflows the structured knowledge needed to investigate and reason more effectively.
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Unsupervised Anomaly Detection
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Security Data Analytics
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Agentic SOC Enablement
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Cybersecurity Platform Enablement
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AI-Ready Data Foundation
AI-Ready Data Foundation
Create reusable security knowledge that can support multiple analytics, detection, and AI workflows.
Works in Parallel with your Existing Data Stack
Knowledge Grid is designed to complement existing security and data architectures. It does not require organizations to replace their data pipelines, SIEMs, data lakes, lakehouses, cloud storage environments, EDR/XDR tools, or cybersecurity applications.
Instead, Knowledge Grid adds a transformation Layer between fragmented telemetry and the applications that need better context. This layer creates reusable knowledge structures that support analytics, anomaly detection, AI workflows, and partner-delivered services.
Knowledge Grid sits in parallel with your existting data stacks and does not need to displace existing data structures.
Build the AI-Ready Foundation for Cybersecurity
Security data is too important to remain fragmented, noisy, and difficult for machines to use. Knowledge Grid transforms telemetry into structured knowledge so security teams, platforms, and AI workflows can detect, analyze, and act with better context.