The Missing Data Layer for Cybersecurity AI
The Temporal Data Grid transforms fragmented security telemetry into structured, time-aware knowledge that AI systems, analytics tools, and security teams can actually use.
The Temporal Data Grid is the patented technology beneath the Cognitive Data Layer. It provides 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.
Explore How It WorksWhat Is the Temporal Data Grid?
In plain terms, the Temporal Data Grid is the data structure that makes the Cognitive Data Layer possible. Where a conventional index stores each event as a row to be searched later, the grid records how entities — users, hosts, applications, network services — behave over time and how those behaviors relate to one another. It builds temporal histograms, feature summaries and correlation structures as telemetry is ingested, using patented approximate query processing and compressed metadata so those structures stay small and fast even at very high data volumes. The outcome is a compact, continuously updated model of the environment that can answer questions such as “is this normal for this host at this hour?” without rescanning raw logs. Analysts, anomaly-detection models and AI agents all query the same grid, which is why Knowledge Grid describes it as the missing layer between raw telemetry and machine reasoning.
The Temporal Data Grid is one of three core structures of the Knowledge Grid Cognitive Data Platform. It converts security telemetry into reusable knowledge structures that preserve meaning, context, relationships, behavior, and time.
Traditional data platforms help organizations collect and query data. The Cognitive Data Layer helps machines and analysts understand it.
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.
The Cognitive Data Layer turns security telemetry into machine-usable knowledge.
1. TELEMETRY
Raw security data from across your environment
- Endpoints / EDR
- Identity & Access
- Network & Security
- Cloud Platforms
- Applications
- Logs & Events
- Databases
- Third-Party Tools
2. CONTEXT
We add meaning by organizing and enriching the data
- Normalize & Standardize
- Entity Resolution
- Enrichment
- Correlation
- Time Alignment
- Deduplication
- Source Attribution
3. KNOWLEDGE STRUCTURES
We convert context into reusable, time-aware knowledge
- Knowledge Descriptions
- Feature Summaries
- Temporal Histograms
- Correlations & Relationships
- Semantic Enrichment
- Behavioral & Entity Context
4. DATA SCIENCE WORKBENCH
We apply advanced analytics and machine learning to discover insights
- Feature Engineering
- Anomaly Modeling
- Unsupervised Detection
- Behavioral Baselines
- Pattern Discovery
- Model Optimization
- Evaluation & Validation
5. INTELLIGENCE
AI-ready intelligence for security teams and automated workflows
- High-Signal Detections
- Actionable Insights
- AI / Agent Recommendations
- Automated Responses
- Operational Intelligence
Feedback
Outcomes
& Behaviors
CONTINUOUS LEARNING LOOP
We continuously learn from feedback and outcomes to improve knowledge and models over time.
Works in Parallel with your Existing Data Stack
The KG Cognitive Data Platform is designed to complement existing security and data architectures. It does not require organizations to replace their existing 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, and AI workflows.
1. SECURITY DATA SOURCES
Diverse. Distributed. Fragmented.
Ingest via APIs,
connectors or
cloud storage
2A. YOUR EXISTING DATA STACK
Stores, manages, and supports traditional analytics and operations.
DATA PLATFORMS
TRADITIONAL & MODERN CAPABILITIES
Built for: Storage · Search · Reporting · Dashboards · Operations
2B. KNOWLEDGE GRID PLATFORM (IN PARALLEL)
Adds the missing Cognitive Data Layer for AI-ready security intelligence.
Cognitive
Data Layer
Transforms fragmented telemetry into time-aware, behavioral, and relational context.
Knowledge
Structures
Creates reusable representations of entities, activity, relationships, and behavior.
Data Science
Workbench
Applies feature engineering, anomaly modeling, and scoring to turn knowledge into intelligence.
Security Intelligence
& AI Workflows
Delivers high-signal intelligence for detection, investigation, and agentic workflows.
Continuous Learning Loop
Outcomes, feedback, and new patterns continuously refine models and knowledge structures.
Delivers
AI-ready
intelligence
3. CONSUMERS & OUTCOMES
Actionable intelligence for people and AI.
Anomaly Detection Security Data
Analytics Agentic SOC
Workflows Cybersecurity
Platforms Reports & Insights APIs & Integrations
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.
AI-Ready Data Foundation
Create reusable security knowledge that can support multiple analytics, detection, and AI workflows.
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.