HOME>PLATFORM>INTEGRATIONS

Cybersecurity Data Integrations

Connect Security Telemetry, Partner Platforms, and AI-Ready Knowledge

Knowledge Grid integrates with the security tools, telemetry sources, and data infrastructure you already use — no need to replace your SIEM, data lake, cloud platform, or analyst workflows.

It sits in the white space between raw telemetry and AI-ready security knowledge.

It organizes time, behavior, relationships, anomalies, and context — so security teams, data scientists, partners, and AI systems can reason over complex environments with greater clarity.

SOURCES IN

SIEMs & data lakes EDR / XDR Cloud platforms Identity providers APIs & connectors

Knowledge Grid

Transforms telemetry into time-aware knowledge at ingest — no pipeline replacement

KNOWLEDGE OUT

SIEM / SOAR Agents & copilots Analytics & BI Threat hunting APIs & notebooks
HOW KNOWLEDGE GRID INTEGRATES

Flexible Integrations

Knowledge Grid supports a range of integration models depending on the customer environment, partner architecture, and data source requirements.

Common integration patterns include:

Cloud storage ingestion
Secure file or object-based data transfer
API-based ingestion
Partner platform integration
Security telemetry exports
Customer-specific data pipelines
Structured and unstructured log ingestion
AI-agent and workflow telemetry where supported

The goal is to make integration practical, secure, and adaptable. Customers can begin with targeted telemetry sources for a specific use case, then expand over time as additional data sources, workflows, and analytical needs emerge.

FEATURED INTEGRATION

DragonFly Cyber + Knowledge Grid

Turning Internal Attack Surface Visibility into AI-Ready Security Knowledge

DragonFly Cyber helps organizations gain visibility into internal attack surface risk, including authentication exposure, encryption posture, certificate health, internal communication paths, governance drift, and other high-value security signals.

Knowledge Grid extends that visibility by transforming DragonFly Cyber telemetry into structured, time-aware knowledge that can be analyzed across context, relationships, behavior, and change. This enables deeper anomaly detection, stronger operational understanding, and a more reliable foundation for AI-assisted security workflows.

Together, DragonFly Cyber and Knowledge Grid help security teams move beyond isolated findings and static dashboards toward a continuously evolving understanding of risk across the environment.

Talk to Us About DragonFly

DRAGONFLY CYBER

Discovery

Discover & observe AI activity

AI usage discovery Shadow AI detection Prompt & interaction monitoring Governance & policy visibility AI risk & exposure monitoring Real-time AI telemetry

KNOWLEDGE GRID

UAD Service

Unsupervised anomaly detection

Unknown & emerging AI behaviors No training data or rules required Entity & relationship anomalies Temporal knowledge modeling Behavioral analytics & risk scoring Explainable anomaly context

TOGETHER, THEY DELIVER

Unified AI visibility

AI usage, users, workflows and risk posture in one place.

Unsupervised anomaly detection

Unexpected AI behavior found without predefined rules.

Continuous governance

Policy drift, misuse and exposure monitored over time.

Risk prioritization

High-risk anomalies ranked by business impact and context.

Designed for Technology Partnerships

Knowledge Grid is designed for cybersecurity vendors, MSSPs, MDR providers, AI security platforms, and other technology partners that want to add AI-ready knowledge, anomaly detection, and data science capabilities to their existing offerings.

Partners can use Knowledge Grid to enhance their own platforms and services without rebuilding the underlying data framework required for large-scale behavioral analysis.

For partners, Knowledge Grid provides the cognitive data layer behind the scenes — helping transform telemetry into structured knowledge that can power higher-value services and differentiated customer outcomes.

Talk to Our Partner Team

Partner integration opportunities include:

Embedded anomaly detection
Private-label or OEM service delivery
Partner-branded analytics offerings
AI-ready security data infrastructure
Data science workbench capabilities
Behavioral baselining and drift detection
Customer-specific knowledge modeling
Security telemetry enrichment and normalization
Integration into existing dashboards, portals, or service workflows