RavenVISION: Visibility + Observability

Healthcare systems accelerate digital transformation and digital health innovation with complete, end-to-end visibility.  

 

Many healthcare organizations look at data intelligence only within the individual IT “silos” for which each set was created. The disjointed approach creates teams of IT experts looking at security, infrastructure, operations, and network from varying points of view and priorities. Overall security, application up time, infrastructure performance, network performance and cost are often viewed as competing priorities among teams. 

“You can’t protect what you can’t see.” RavenTek Health believes enterprise visibility and observability is the foundation for every cybersecurity program. An observability gap occurs when many visibility datasets remain in individual silos, whereas a visibility gap occurs when critical telemetry information is missing from any one of those silos. 

RavenVISION: Visibility + Observability

RavenTek has developed the RavenVISION methodology to help healthcare organizations identify gaps and overlaps in data, maximize use of existing IT investments, and aggregate all enterprise visibility datasets. The RavenVISION Observability Data Value Chain provides deep visibility into the integration of security, infrastructure, operations, and network datasets. Feeding rich, observability across the entire environment and feed zero trust risk assessment algorithms and train Machine Learning models to predict, prevent, respond, and protect enterprise data.

RavenVISION: Accelerating Innovation and Securing The Patient Experience.

RavenVISION: Visibility + Observability

RavenTek RavenVISION is the Intelligent Visibility Integration of Security Infrastructure, Operations and Network into a single AI/ML driven data intelligence platform for enterprise observability. 

The RavenVISION Service mission is to create Centers of Excellence for Observability by working across traditional IT silos and aggregating their data to build an IT Mission Statement focused on proactive security and end-to-end service sustainment. 

Provide a centralized AI/ML driven team for monitoring and response with continuous and dynamic enhancement to policy and process automation 

Develop a consolidated roadmap to increase compliance. 

Use AI/ML in real-time with ALL DATA to power Dynamic Risk Scoring to more securely inform trust algorithms 

Enable Dynamic Policy decisions and enforcement with automated intelligence in line with the latest cybersecurity frameworks