Digi International released DANI (Digi Artificial Network Intelligence), an AI network operations agent embedded directly into its Digi Remote Manager (DRM) device management platform, on July 10, 2026. The move puts conversational AI diagnostics inside the same system operations teams already use to manage device fleets - eliminating the need to switch tools, move data, or manage separate credentials when troubleshooting network issues.
DANI uses the Model Context Protocol (MCP) to access real-time device telemetry, cellular signal data, firmware state, and configuration history directly within DRM. That native integration means diagnostics run against live operational data without exporting logs or granting third-party access. For operations teams managing hundreds or thousands of distributed devices, the speed difference between asking a plain-language question and manually correlating logs across systems is measured in hours per incident.
What DANI can do inside the platform
The agent supports conversational diagnostics - operators type questions in plain language and receive actionable answers without manual log analysis. Continuous device health monitoring identifies anomalies early and surfaces potential issues before they affect operations. DANI also generates intelligent recommendations for firmware updates, configuration fixes, and performance optimization based on real-time network data.
Routine management tasks can be automated directly through the interface, reducing manual workload and improving consistency across device fleets. For managed service providers, multi-tenant support handles large-scale deployments across multiple customers without cross-contamination of data or configurations. No additional infrastructure, separate login, or data movement is required.
Native integration vs. bolt-on AI tools
Most AI network tools sit outside the management platform, requiring API connections, credential sharing, and data export pipelines. DANI operates within the same system that manages the devices, which Digi said results in faster diagnostics with fewer security touchpoints. The architecture reflects a broader shift in operational technology: moving intelligence to where the data already lives rather than pulling data into an external AI layer.
Tony Puopolo, President of Digi Managed Solutions, said: "AI is reshaping how critical infrastructure is managed, and the next phase of networking will be defined by systems that can interpret, decide and even act in real time, if given explicit permissions. DANI represents a foundational shift for industry. By embedding AI directly into the operational fabric of our cloud platforms, we are moving beyond visibility in a major step toward true network autonomy, giving operators the context, scale, and real-time insight needed to transform how networks are managed. This truly reduces the cost and complexity to deploy, manage and support new networks."
From reactive firefighting to proactive operations
The practical impact for operations teams is a shift in workflow. Instead of receiving an alert, pulling logs, switching to a diagnostic tool, and manually tracing root cause, an operator can ask DANI what changed and receive a contextual answer in seconds. The system understands device telemetry, network behavior, and Digi-specific operational workflows - knowledge that would otherwise require senior technicians to accumulate over years.
For network administrators adapting to AI-augmented workflows, structured training through an AI Learning Path for Network Administrators can bridge the gap between traditional device management and AI-assisted operations. The same skills that make someone effective at manual troubleshooting - pattern recognition, systematic diagnostics, configuration discipline - become force multipliers when paired with an AI agent that handles data correlation at scale.
Why this matters for operations professionals
Every hour spent correlating logs across systems is an hour not spent on architecture improvements, security hardening, or capacity planning. DANI automates the diagnostic middle layer - the part of the job that involves gathering and interpreting raw telemetry - and leaves operators with actionable conclusions. For teams running lean, that changes the math on how many devices one administrator can effectively manage. Digi has not published pricing or availability details beyond what is listed on digi.com.
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