The KG Cognitive Data Platform is a three-pillar architecture purpose-built to transform high-velocity security telemetry into structured, AI-ready data. Protected by 7 issued patents.
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Make security telemetry AI-ready without replacing your stack
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Built for Agentic AI - Day one (No additional Data Transformation)
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Find the threats modern security tools structurally cannot detect
The AI Data Platform for Cybersecurity
The Problem: Security Data was Not Built for AI
Most security stacks were designed for storage, search, dashboards, and human investigation. They were not built to convert massive, fragmented telemetry into machine-usable knowledge for AI-driven analysis and autonomous operations.
The Architecture Problem
Traditional Data Stacks
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Traditional data pipelines were built for human analysts, dashboards, and rule-based detections.
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AI requires something different: structured relationships, temporal context, and optimized data representations that help models understand what changed, what matters, and what to prioritize.
The Operations Problem
Too Much Data, Too Little Context
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Security teams have no shortage of data, but most of it lacks the structure, correlation, and temporal context AI needs to generate reliable insights.
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Without that optimization layer, AI models are forced to process noisy inputs that reduce accuracy, slow down outputs and increase cost.
The analytics Problem
Data is Fragmented Across Too Many Systems
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Critical security insights are spread across multiple tools, formats, and storage layers.
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This fragmentation makes it difficult for AI to reason across the full picture, connect patterns over time, and produce reliable outputs.
Why Traditional Data Stacks Fall Short
Traditional data stacks fall short because they store and retrieve security data, while the Cognitive Data Grid transforms telemetry into time-aware, AI-ready context that reveals behavior, relationships, and change over time.
What Knowledge Grid Does
Knowledge Grid is the Cognitive Data Grid for cybersecurity AI — we transform raw security telemetry into structured, high-signal, contextual knowledge that is AI-optimized for upstream LLM applications and agentic workflows.
Detect Unknown Threats
Find hidden threats you do not know to look for using Unsupervised Anomaly Detection (UAD).
Improve AI Context & Outcomes
Give AI agents structured knowledge, while reducing noise and improving LLM outcomes using enriched data models.
Reduce Data Stack Friction
Create reusable knowledge structures that reduce dependence on repeated queries across SIEMs, data lakes, lakehouses, indexes, and tables.
Architecture - Platform Pillars
Pillar 1 — Temporal Data Grid
The foundational data transformation engine. Built on patented Rough-Set mathematics, the Temporal Data Grid ingests high-velocity security telemetry and transforms it into structured, AI-queryable representations at 10–100x the performance of legacy database architectures.
Core capabilities: Approximate Query (AQ), NoSQL Full Log Line Search, Automated Key-Value Pair structuring, Pluggable Knowledge Nodes, and Semantic Enrichment at ingest.
Pillar 2 — Data Science Workbench
The AI and analytics enablement layer built on top of the Temporal Data Grid. The Data Science Workbench provides the tools that allow AI models, data scientists, and security analysts to work with security telemetry effectively.
Core capabilities: Natural Language Interface (KGQL), Hyper-Scalable Vector Database, Automated Feature Selection, Derived Keys and Feature Store, Jupyter Notebook integration, and a suite of Agentic AI automation capabilities for SOC workflows.
Pillar 3 — Anomaly Detection & Analysis
The flagship use case built directly on Pillars 1 and 2 — and a competitive differentiator in its own right. Fully unsupervised detection of threats no signature or rule will ever catch.
No training data, no human-defined rules, no prior threat knowledge required. Detects six anomaly types: Volumetric, Zero-Day, Reverse, Diversity, Distinctive, and Dimensional. Three generations of threat scoring. Investigation narratives generated by Agentic AI.
Cognitive Data Grid Platform Overview
We convert fragmented telemetry into reusable, AI-ready knowledge structures
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Turn telemetry into knowledge — Convert fragmented security data into structured, reusable context.
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Power AI-ready security workflows — Support anomaly detection, analytics, and agentic SOC use cases.
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Embedded Data Science — allows you to easily integrate upstream analytics without additional post-processing of data
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Improve with every outcome — Built-In feedback mechanisms help to refine the knowledge layer.
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PRIMARY USE CASES
Use Cases Designed & Built for AI-Driven Security
Cyber Security Use Cases
Advanced analytics and detection capabilities built on an AI-ready data foundation (Cognitive Data Layer).
Platform Use Cases
The Cognitive Data Layer, AI-Ready data foundation powers & scales Agentic AI & LLM based solutions
Who We Serve
Helping security teams, service providers, and technology partners turn unstructured & semi-structured security data into optimized, AI-ready security intelligence.
Security Teams
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Eliminate noisy data
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Detect unknown threats faster
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Improve SOC outcomes with better context than what a SIEM provides
MSSP/MDR &
Managed Security
Cyber Security Platform Vendors
AI SOC (Agentic SOC) Providers
Data & AI Infrastructure Partners
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Better Context = Better accuracy
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Lower Compute Cost
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Solve Data Quality problems
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Avoid a costly data stack re- architecture
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Pre-built data science functions speed analytics
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Lower Compute Costs
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Using the Cognitive Data Layer to support SOC agents will
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Bypass data access bottlenecks
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Provide better data context
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Specialized cyber-intelligence layers will enrich upstream agentic workflows
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Avoid costly data re-processing post ingestion
Protected by 7 issued US patents covering the Temporal Data Grid architecture, approximate query processing, compressed metadata structures, and log transformation.
Why Knowledge Grid?
Because AI-driven security needs more than data — it needs structured, contextual knowledge.
A smarter data foundation for - finding security threats, improving data context, & accelerating security workflows.
Knowledge Grid ensures your security telemetry is structured and clean, allowing AI models to operate with maximum accuracy and minimal tuning overhead.
AI-Ready Data Foundation
By tracking how identities and assets evolve over time, the platform gives your security teams the historical perspective needed to dismiss false positives instantly.
Temporal and Behavioral Context
Our platform is engineered by practitioners who understand real-world SOC friction, combined with data scientists pioneering the use of Rough Set Theory for cyber security.
Designed for seamless integration with your existing MSSP or security stack, ensuring you get immediate value without complex re-architecting.
Uncover sophisticated, cross-vector threats that signature-based tools miss by analyzing complex relationships across your entire infrastructure.
Multidimensional Anomaly Discovery
Built by Operators and Scientists
Partner-Ready Delivery Model
Our Advantage
Scientific Background
Research & Development
Knowledge Grid was built by a team with deep expertise in data science, big data architecture, and cybersecurity operations. Our platform is supported by an advanced research and development team based in Warsaw, Poland, with specialized experience in mathematical modeling, large-scale data processing, AI, Data Classification, and machine intelligence.
At the core of our technology is deep expertise in Rough Set Theory, the mathematical foundation behind our Temporal Data Grid, unsupervised anomaly detection, and advanced knowledge structures. This foundation enables Knowledge Grid to transform complex, high-volume data into machine-usable context, helping AI systems analyze, reason over, and interpret dynamic data with greater speed and precision.
Featured Resources
Access the latest insights on cognitive data architecture and security telemetry optimization.
Cognitive Data Layer Explainer
Understand how our intelligence layer transforms raw telemetry into machine-usable knowledge.
UAD Overview
A deep dive into Unsupervised Anomaly Detection and finding threats signature-based tools miss.
AI-Ready Data Infrastructure Survey
Evaluate your current stack readiness for agentic SOC and autonomous security workflows.
Partner Brief
A guide for MSSPs and technology vendors looking to integrate the Knowledge Grid layer.