Every enterprise is adopting AI. That's no longer a prediction, it's a line item on the budget. But here's the question I keep coming back to: most of these AI investments are talking about your network. How many of them are actually talking to it?
At Digi, we've been sitting with that question for a while. And the answer we landed on starts not with a chatbot, but with something more fundamental: an open, standards-based foundation that makes your entire Digi network accessible to the AI tools you already use.
We call the initiative DANI, or Digi Artificial Network Intelligence. Let me walk you through what we built and why we built it the way we did.
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AI Overview
DANI: An Open MCP Foundation That Makes Your Digi Network AI-Ready
DANI (Digi Artificial Network Intelligence) is Digi’s open, standards-based approach to connecting the AI platforms you already use — including ChatGPT, Claude, Copilot, Gemini, and other MCP-compatible systems — directly to your Digi environment. Instead of introducing another closed AI console, Digi provides a hosted Model Context Protocol (MCP) Server that exposes your Digi fleet — devices, telemetry, logs, firmware status, alerts, and analytics — through a standardized interface so your preferred AI can securely query and reason over real network data.
Open standard (MCP) Works with your AI platform Fast setup (~5 minutes) Read-only by design (today) Built for AIOps + IoT fleets
What problem does DANI solve?
Many AI features in networking environments provide dashboards or documentation assistants — but they don’t truly operate on live network data across systems. DANI enables AI-assisted operations across cellular IoT and distributed fleets by making Digi Remote Manager and Digi Ventus Genesis accessible to any MCP-compatible AI. Engineers can ask: “Which devices went offline in the last 24 hours, and what do their event logs show?” — and receive synthesized, context-aware answers based on real-time data.
Why MCP-based architecture matters
- Your AI, your choice: Use the AI model your organization has already standardized on.
- Integration, not isolation: Build agents that connect Digi operations with ticketing, cloud, and other vendors.
- Future-proof foundation: As AI models evolve, MCP remains the connective layer.
- Scalable economics: You use your own AI account and token budget while Digi hosts the MCP endpoint.
Available now for Digi Remote Manager and Digi Ventus Genesis customers. Initial MCP endpoints are read-only by design. An in-app DANI Agent with expanded capabilities, including write operations and proactive management, is on the roadmap.
DANI is designed for enterprise IT teams, network operations leaders, and managed service providers managing distributed cellular IoT fleets who want AI-assisted diagnostics, reduced mean time to resolution, and scalable operational visibility without vendor lock-in.
The AIOps market is exploding, somewhere between $16 billion and $28 billion today depending on how you draw the boundaries, and virtually every forecast projects it will more than double within five years. The forces driving that growth are well understood: IT environments are growing more complex, skilled network engineers are harder to find, and the volume of telemetry data generated by connected devices has long since exceeded what human operators can process manually.
In cellular IoT and distributed network management (our world), those pressures are amplified. Branch routers, industrial gateways, transportation systems, critical infrastructure endpoints. They generate enormous volumes of signal strength data, connection events, firmware status updates, and configuration drift. Managing fleets of hundreds or thousands of these devices demands automation. Managing them intelligently demands AI.
Our competitors recognize this. Across the networking industry, vendors have been racing to ship AI features, mostly chatbots that answer documentation questions, dashboards with predictive analytics, and autonomous troubleshooting agents. Some of these capabilities are genuinely useful. But nearly all of them share a fundamental architectural limitation: they're closed systems.
Here's what I mean. When a vendor builds an AI assistant that lives exclusively inside their management console, they're solving their problem, not yours. Your network doesn't exist in isolation. Your Digi routers sit alongside switches, firewalls, cloud services, and custom operational tools from a dozen other providers. An AI that can only see one piece of that picture isn't an operations partner, it's a silo with a chat interface.
We decided to build something different.
Instead of starting with a chatbot, we started with the infrastructure that makes any AI — ours, yours, or the next breakthrough model that hasn't been released yet — capable of understanding and interacting with your Digi network.
The foundation is our MCP (Model Context Protocol) Server, a hosted endpoint built on the Model Context Protocol, the open standard that's rapidly become the universal language for connecting AI systems to real-world tools and data. MCP has been adopted by every major AI platform, including Anthropic's Claude, OpenAI's ChatGPT, Microsoft's Copilot, and Google's Gemini which is now hosted as an open source project by the Linux Foundation. When we say, "open standard," we mean it.
Here's what that looks like in practice: instead of writing thousands of lines of custom API integration code to teach an AI about Digi Remote Manager or Digi Ventus Genesis, you point your AI platform at our MCP endpoint, authenticate with an API key, and you're connected. The AI immediately understands how to query your devices, pull telemetry data, review event logs, check firmware status, examine alert configurations, and navigate your entire fleet, all through natural language.
Setup takes about five minutes. Not weeks. No sprints. Minutes.
This architectural choice is deliberate, and it reflects how we think about our customers' real-world operations.
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Your AI, your choice. Many of our partners and enterprise customers have already standardized on an AI platform. They're running Claude, GPT, or Copilot across their organizations. They don't want *another* AI to manage; they want their existing AI to do more. The Digi MCP Server makes that possible. Connect the tools you already trust for the network you already run.
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Integration, not isolation. Managed service providers and sophisticated enterprise teams don't manage Digi devices in a vacuum. They've built operational portals that integrate monitoring, ticketing, and automation across multiple vendors and platforms. The MCP Server fits cleanly into those workflows. An MSP can build a single AI agent that talks to their Digi fleet, their cloud infrastructure, their ticketing system, and their customer database, all through the same standardized protocol.
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Future-proof by nature. AI is moving fast. The best model today may not be the best model six months from now. (And if the last two years have taught us anything, it's that "six months" might be generous.) By building on an open standard, we've ensured that your investment in connecting AI to your Digi network isn't locked to any single vendor's roadmap, including ours. When the next generation of AI tools arrives, they'll speak MCP, and your network will be ready.
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Economics that scale. Here's a practical reality that matters: when your AI connects to Digi MCP Server, you're using your own AI account and your own token budget. We're not metering AI queries or charging per-conversation. We host the server. You bring the intelligence. That's a model that scales sustainably for everyone.
The breadth of what our MCP Server exposes is substantial. We've built dozens of tools spanning device management, telemetry and data streams, remote device operations, alerting and monitoring, automation workflows, firmware management, configuration templates, audit trails, user and account management, and comprehensive fleet analytics.
That's not a thin wrapper around an API. It's a purpose-built interface designed for how AI systems actually reason about problems. When a network engineer asks their AI, "Which devices went offline in the last 24 hours and what do their event logs show?", the AI doesn't just return a data dump. It discovers the right tools, calls them in the right sequence, synthesizes the results, and delivers an answer in plain language.
You can connect to a live Digi MCP Server environment and watch it diagnose network issues in real time. Within seconds, you can see what's offline, review event logs, and determine whether a device has been physically unplugged. Real diagnosis. Real data. Real-time.
That's the difference between an AI that reads your documentation and one that reads your network.
I want to be direct about what's shipping and what's on the roadmap, because I think transparency matters more than hype.
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Available now: The Digi MCP Server for Digi Remote Manager. We are also releasing the Digi MCP Server for Digi Ventus Genesis, built on the same MCP foundation, purpose-tuned for network operations. These are hosted, API-key-authenticated MCP endpoints that give any compliant AI platform full read access to your monitoring and management environment. They are read-only by design. We started with operations that can't break anything. Trust is earned, and that's true for AI just like it's true for people.
The MCP Server is the foundation. The DANI Agent, when it releases, will be the experience layer on top: an AI that doesn't just answer questions about your network, but reasons about problems, recommends actions, and ultimately becomes a true network operations partner. One that knows your Digi network better than anyone.
But I'm not going to promise the car before the engine is running. What we're delivering today is the infrastructure that makes everything else possible, and it's already the most capable AI integration point in cellular IoT network management.
The IT skills gap isn't closing. Over three-quarters of companies report technology talent shortages, and the problem is getting worse year over year. AI doesn't replace your network engineers; it multiplies them. It lets your best people focus on the work that requires their expertise, while AI handles the "which devices are offline" and "what's the firmware status of my sites" type of questions that consume their days.
Teams that free their engineers from repetitive diagnostic work can redirect expertise toward architecture, optimization, and growth. Studies consistently show AI-assisted diagnostics can cut mean time to resolution by 30 to 50 percent and reduce support escalations by 15 to 25 percent. Those aren't hypothetical numbers; that's what happens when your AI can actually see your network instead of just reading about it.
The Digi MCP Server makes your Digi network AI ready today. Any AI. Any workflow. Your network.
You don't have to wait for us to build the perfect AI assistant. You can use the one you already trust. We just made sure it can talk to your network.
So — what would you ask your network if it could answer?
The Digi MCP Server is available now for Digi Remote Manager and Digi Ventus Genesis customers. Contact your Digi account representative or reach out to our team to get started!
What is DANI (Digi Artificial Network Intelligence)?
DANI — Digi Artificial Network Intelligence — is Digi's AI ecosystem. At its foundation is a hosted MCP Server that connects your AI platform to your Digi network, giving it access to device telemetry, event logs, firmware status, alerts, and fleet analytics through natural language.
Is the Digi MCP Server read-only?
Yes. The current MCP endpoints provide read-only access to monitoring and management data. This design prioritizes operational safety and trust. Expanded capabilities are planned in the upcoming DANI Agent experience layer.
Who should use DANI?
DANI is designed for enterprise IT teams, network operations leaders, and managed service providers managing distributed cellular IoT fleets who want AI-assisted diagnostics, reduced mean time to resolution, and scalable operational visibility without vendor lock-in.
How is access to the Digi MCP Server secured?
Access to the Digi MCP Server is authenticated and scoped to your Digi environment. The current implementation is read-only by design, ensuring AI systems can analyze monitoring and management data without making configuration changes.
Do I need to adopt a new AI platform to use DANI?
No. DANI is designed to work with the AI platform your organization already uses, as long as it supports the Model Context Protocol (MCP). You connect your existing AI tool to the Digi MCP Server and begin querying your Digi network immediately.
What kinds of network questions can I ask through DANI?
You can ask operational questions such as:
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Which devices went offline in the last 24 hours?
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What firmware versions are running across my fleet?
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What do the event logs show for this site?
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Are any devices experiencing repeated connectivity drops?
The AI uses MCP tools to retrieve and synthesize real-time data from your Digi environment.
Can managed service providers (MSPs) use DANI across multiple customer environments?
Yes. MSPs can connect their AI platform to multiple Digi environments using authenticated MCP endpoints. This enables the creation of unified AI-driven operational workflows spanning multiple customer fleets and infrastructure systems.
How is DANI different from traditional AIOps solutions?
Traditional AIOps tools are often embedded within a single vendor's management console. DANI is built on MCP, the standard adopted by every major AI platform, allowing enterprises to use their preferred AI platform and integrate Digi network data into broader cross-vendor operational workflows.