Ivanti Neurons for Discovery

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Ivanti Neurons for Discovery is a cloud-based solution that delivers real-time IT asset discovery and inventory, mapping devices and dependencies to optimize asset management and security.

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Ivanti Neurons for Discovery is a cloud-native solution that automatically discovers and inventories all IP-connected devices and services across an organization’s network, delivering accurate and actionable asset information in minutes. It uses active and passive scanning, along with third-party connectors, to identify managed and unmanaged devices, including endpoints, servers, IoT devices, and cloud assets, without requiring agents on every device. The platform aggregates data from multiple sources, normalizes hardware and software inventory, and maps dependencies to create a single source of truth for IT assets. Integrated with the Ivanti Neurons hyper-automation platform, it populates configuration management databases (CMDB) and asset management systems, enabling IT teams to optimize asset value, enhance security posture, and improve service delivery. Ivanti Neurons for Discovery is ideal for organizations seeking to eliminate manual tracking, reduce ghost assets, and gain real-time visibility into complex IT environments.

  • Architecture:
    • Components:
      • Ivanti Neurons Platform: Cloud-based platform hosting discovery services, leveraging AI for data normalization and analytics.
      • Discovery Service: Cloud-hosted engine for active/passive scanning and data aggregation.
      • Console: Web-based interface for configuration, dashboards, and reporting.
      • Connectors: Third-party integrations (e.g., Google Workspace, MobileIron) for external data sources.
      • Optional Agent: Lightweight Ivanti Neurons Agent for enhanced inventory on managed devices.
    • Deployment Options:
      • Cloud-Native: Hosted on Microsoft Azure, fully managed by Ivanti.
      • Hybrid: Cloud-based discovery with on-premises connectors for restricted networks.
    • Scalability: Supports millions of assets; scales seamlessly with cloud infrastructure.
    • Operation Mode: Primarily agentless using network protocols (SNMP, WMI, SSH); agent-based for deeper inventory on managed devices.
  • Discovery Methods:
    • Active Scanning: Probes network segments using SNMP, WMI, SSH, or ICMP to identify devices.
    • Passive Scanning: Listens to network traffic (e.g., DHCP, ARP) to detect devices without active queries.
    • Third-Party Connectors: Imports data from Google Workspace, MobileIron, Microsoft SCCM, Active Directory, and more.
    • Self-Organizing Technology: Elects devices to report data, ensuring no duplication or failover issues.
  • Inventory Capabilities:
    • Hardware: Captures CPU, RAM, storage, manufacturer, model, serial number, and network details.
    • Software: Tracks installed applications, versions, and usage (on managed devices).
    • Services: Maps dependencies between assets, applications, and services.
    • Cloud Assets: Discovers assets in AWS, Azure, and Google Cloud environments.
    • Normalization: Aggregates and reconciles data from multiple sources to eliminate duplicates.
  • Authentication:
    • Integration: Azure AD, Okta, Active Directory, SAML 2.0 for SSO.
    • Access Control: Role-based access for admins; supports MFA via Ivanti Neurons MFA.
    • API Security: OAuth 2.0 for connector integrations.
  • Integration:
    • Ivanti Ecosystem: Ivanti Endpoint Manager, Neurons for UEM, Policy Secure (NAC), Neurons for ITSM, Asset Manager.
    • Third-Party: Google Workspace (Chrome Enterprise connector), Microsoft SCCM, Intune, ServiceNow, Splunk, MobileIron.
    • APIs: REST APIs for custom integrations; SCIM for identity provisioning; syslog for event logging.
    • CMDB/Asset Management: Auto-populates ServiceNow, BMC Helix, or Ivanti Asset Manager.
  • Visibility and Reporting:
    • Dashboards: Real-time views of asset inventory, compliance, and service dependencies.
    • Reports: Customizable for hardware/software inventory, software usage, warranty status, and end-of-life tracking.
    • Service Maps: Visualizes asset-to-service dependencies for impact analysis.
    • Analytics: AI-driven insights for asset optimization and risk identification.

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