How Mesh Systems Builds on Azure IoT Hub and Azure IoT Operations to Accelerate Industrial AI

Microsoft

Jul 28, 2026

Manufacturers generate vast amounts of operational data, yet its complexity and fragmentation across historians, Operational Technology (OT) systems, and cloud platforms can slow AI adoption at scale. As organizations invest in AI to enhance productivity, quality, and decision making, the ability to connect and contextualize operational data becomes critical. Azure IoT Hub, Azure IoT Operations, and Mesh address this challenge together, spanning the full path from device connectivity to actionable AI-powered insights.

Mesh brings deep Azure IoT platform experience and a practical path to industrial AI, with MeshCloud built on Azure IoT Hub, an open-source .NET Akri framework for Azure IoT Operations, and MeshInsights delivering generative AI-powered operational intelligence. This expertise is backed by a long history with Azure; Mesh launched its first IoT solution on Azure in private preview in 2009 and remained an early adopter of every major Azure IoT service since.

Together, Azure IoT Hub, Azure IoT Operations, and Mesh give manufacturers a streamlined way to unify operational data and apply AI where it matters most.

Unlocking legacy data with Mesh's Akri Connector

Industrial organizations often struggle to modernize operations because critical operational data sits isolated inside historians and legacy Operational Technology (OT) systems. Many manufacturers are also wary of integrations that create new dependencies and limit future flexibility. Azure IoT Operations addresses this through an open architecture built around Akri, connecting industrial data sources while preserving interoperability across hardware and software environments.

Mesh built on this foundation with its Akri Historian Connector, bringing historian and legacy operational data into Azure IoT Operations through prebuilt connectivity rather than source-by-source integration work. The result is faster access to operational data ready for analytics, AI, and industrial automation.

The key features of this connector include:

Restart-safe data continuity: Manufacturers can trust that operational data keeps flowing even through outages or restarts, with no data loss and no time spent recovering or reprocessing data.
Secure, flexible authentication: Modern and legacy industrial systems connect under one security model, meeting enterprise-grade authentication standards without restructuring existing infrastructure.
A foundation other connectors can be built on: The underlying framework handles the heavy lifting, so teams only need to build what's unique to each new OT data source. This means faster time to value for every new data source.
Built in alignment with Azure IoT Operations roadmap: The connector stays up to date automatically, as new Azure IoT Operations features become available. This means manufacturers have access to the latest capabilities as the platform evolves.

Together, Mesh and Azure IoT Operations give organizations a production-ready path from the shop floor into Azure IoT Operations and onward to Microsoft Fabric.

Delivering Scalable Connected Products with Azure IoT Hub and MeshCloud

MeshCloud helps manufacturers move from connected product pilots to fleet scale deployments faster by providing a platform build on Azure IoT Hub and other Azure native services.

Azure IoT Hub provides per-device identity, support for MQTT, AMQP, and HTTPS, and built-in capabilities like device twins, direct methods, and rules-based message routing. Azure Device Provisioning Service (DPS) extends this foundation with zero-touch, just-in-time onboarding using X.509, TPM, or symmetric key attestation.

Mesh operates as one cohesive engineering practice across the full connected product lifecycle, delivering hardware, firmware, wireless, edge, and cloud integration natively for Azure IoT Hub and Azure IoT Operations. That end-to-end scope is what MeshCloud, their Azure-native connected product platform, brings together.

MeshCloud embeds Azure IoT Hub and DPS into an Azure-native connected product platform, giving organizations a faster path to connected product delivery without sacrificing control, scale, or solution ownership. The platform comes together across four layers:

Edge to cloud: Connected devices, from MCU controllers to tablets and phones, register and authenticate through DPS and connect securely to IoT Hub, giving organizations a direct, secure line from shop floor to enterprise systems.
Messaging and command: Event Hubs and Container Apps move telemetry and commands between devices and the cloud, with asset and ontology data exposed for digital twin management and device control.
IT and operations: Azure Monitor, OpenTelemetry, Microsoft Entra, and Application Gateway bring platform observability, identity management, and secure ingress together, equipping IT and operations teams with a unified way to manage and secure the environment.
Analytics and visualization: Telemetry flows into Azure Data Explorer and Microsoft Fabric for processing and storage, with Grafana, Power BI, and a Device Health UI giving teams fleet-wide visibility.

This architecture enables organizations to move from pilot projects to fleet-scale deployments using Azure-native services, while maintaining interoperability across devices, connectivity protocols, and analytics platforms. For manufacturers, this means less time integrating infrastructure and more time delivering operational insights, connected services, and AI-powered workflows.

Advancing Industrial Intelligence with MeshInsights

As organizations connect more assets and operational systems, the next challenge becomes turning information into consistent actions and decisions. Microsoft Azure provides the cloud, data, and AI foundation for intelligent operational workflows, while giving organizations control over their data and business processes. Mesh extends this foundation through MeshInsights.

MeshInsights is Mesh's AI agent offering for connected-product manufacturers. Mesh works with organizations to define a specific operational decision worth automating, such as classifying an alert or determining the right service response, and builds an evaluation standard from real telemetry, service history, and expert-validated examples. AI agents are then developed and measured against that standard, acting automatically on high-confidence cases and routing the rest to the organization's own experts. This extends connected systems beyond monitoring and reporting into trusted, auditable operational decisions.

By combining Azure IoT platform services with MeshInsights, Mesh helps organizations move from connected infrastructure to autonomous, AI-driven action without changing where their data lives or who owns the architecture.

Why This Matters

Industrial transformation increasingly depends on strong collaboration between hyperscale cloud platforms and ecosystem partners who bring operational expertise, deployment acceleration, and industry-specific engineering capabilities.

Mesh Systems demonstrates how partners can build differentiated value on top of Azure IoT platform services while helping organizations accelerate deployment timelines, standardize industrial data architectures, and operationalize AI across connected environments.

Organizations are already putting this value to work in everyday operations. BUNN's cloud-connected coffee machines now give technicians a head start before every service call. As Kurt Powell, Executive Vice President at BUNN, put it: "With this solution, we know exactly which component to fix before we get there." WLS Lighting Systems has turned that same visibility into measurable savings at scale. Built on MeshCloud and Azure IoT, WLS's netLiNK gives property owners remote monitoring and control over individual light fixtures. Kevin Fletcher, President National Accounts at WLS, shared that the company has saved customers a little over $50 million in electrical costs since bringing netLiNK to market.

Together, Azure IoT Hub, Azure IoT Operations, and Mesh Systems help manufacturers reduce integration complexity and operationalize industrial data, creating a foundation for AI driven operations spanning plant, edge, and cloud. The result: manufacturers spend less time on integration and more time improving productivity, resiliency, and decision making across their operations.