Ennetix, Inc.
Provider of an AIOps-based unified observability platform and endpoint agent that combine network, application and security telemetry with AI/ML analytics to enable real-time detection, root-cause analysis, and automated remediation across cloud, on-prem and hybrid IT environments. The platform exposes situational awareness through entity inventories, session-level connection analysis, and contextual threat insights to support investigation and remediation across IT and OT environments.
Industries
N/A
Nr. of Employees
small (1-50)
Ennetix, Inc.
Products
AIOps unified observability platform
Platform that ingests diverse telemetry sources, applies AI/ML analytics for anomaly detection and root-cause analysis, and supports automated remediation workflows and compliance reporting.
Endpoint observability agent
Cross-platform agent that collects process, network connection, command execution and provenance data from endpoints to support forensics, security monitoring and compliance.
AIOps unified observability platform
Platform that ingests diverse telemetry sources, applies AI/ML analytics for anomaly detection and root-cause analysis, and supports automated remediation workflows and compliance reporting.
Endpoint observability agent
Cross-platform agent that collects process, network connection, command execution and provenance data from endpoints to support forensics, security monitoring and compliance.
Services
Implementation, integration and managed deployment of unified observability and AIOps solutions across cloud, hybrid and on-prem environments.
Deployment and configuration of synthetic probes and active monitoring agents to measure latency, jitter, loss and bandwidth from access points and endpoints for end-user experience validation and troubleshooting.
Implementation, integration and managed deployment of unified observability and AIOps solutions across cloud, hybrid and on-prem environments.
Deployment and configuration of synthetic probes and active monitoring agents to measure latency, jitter, loss and bandwidth from access points and endpoints for end-user experience validation and troubleshooting.
Expertise Areas
- Unified observability across network, application, endpoint and security domains
- AIOps and agentic AI for operations
- AI-driven remediation and self-healing operations
- Root-cause analysis with multi-source correlation
Key Technologies
- AIOps platforms
- Agentic AI / autonomous agents
- Machine learning and deep learning (temporal models for session data)
- Explainable AI / operator-facing model explanations
News & Updates
Overview of core observability data types and their role in modern distributed systems.
Discussion of security observability and its importance for hybrid IT environments and situational awareness.
Explains agentic AI concepts for observability and autonomous remediation in IT operations.
Describes AI-driven detection, root-cause analysis and automated remediation to minimize downtime.
Practical guidance on what to expect from AIOps solutions and the importance of explainability and human-in-the-loop adoption.
Case study demonstrating session-level connection analytics, entity inventories and detection of anomalous SSH/HTTP behaviors to support incident investigation.
Overview of core observability data types and their role in modern distributed systems.
Discussion of security observability and its importance for hybrid IT environments and situational awareness.
Explains agentic AI concepts for observability and autonomous remediation in IT operations.
Describes AI-driven detection, root-cause analysis and automated remediation to minimize downtime.
Practical guidance on what to expect from AIOps solutions and the importance of explainability and human-in-the-loop adoption.
Case study demonstrating session-level connection analytics, entity inventories and detection of anomalous SSH/HTTP behaviors to support incident investigation.