ThingWorx 10.0 and Microsoft Azure: Powering Industrial IoT From Edge to Insight | Velotic
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ThingWorx 10.0 and Microsoft Azure: Powering Industrial IoT From Edge to Insight

Discover how Velotic's ThingWorx 10.0 and Microsoft Azure transform industrial IoT by unifying edge-to-cloud data, AI, and analytics for smarter operations.

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Velotic’s ThingWorx and Microsoft Azure empower organizations to excel in end-to-end industrial data management, seamlessly bridging the gap from data acquisition to actionable insights. By combining Velotic's Kepware for robust device connectivity, the ThingWorx IIoT platform for real-time data contextualization, visualization, and AI built on top of Microsoft Azure’s scalable cloud infrastructure, businesses can accelerate their digital transformation within a unified, high-performance ecosystem.

With ThingWorx 10.0, Velotic customers can leverage IoT streams to seamlessly make access for ThingWorx contextualized IoT data into Microsoft Fabric’s One lake for data lake and advanced analytics use cases. This integrated approach empowers organizations to unlock the full potential of their industrial data, driving smarter decisions and transformative outcomes.
IoT Streams: enabling ThingWorx for end-to-end industrial data management

IoT Streams: Enabling ThingWorx for end-to-end industrial data management

ThingWorx 10.0 introduces IoT Streams, a feature that empowers users to extract contextualized IoT data using Kafka or managed Kafka services like Azure Event Hubs. This durable message broker facilitates seamless data streaming to data lakes, cold archival storage, or third-party systems, while ensuring real-time access to critical data within ThingWorx. With built-in security and role-based access control, IoT Streams provides a secure and efficient way to integrate industrial data with external tools, enabling advanced analytics and industrial data management use cases.
Microsoft Fabric: data analytics platform for AI-driven innovation

Microsoft Fabric: Data analytics platform for AI-driven innovation

Microsoft Fabric is an all-in-one SaaS analytics platform that seamlessly unifies data integration, storage, governance, and analysis. At its core is OneLake, a single, logical data lake that consolidates streaming and historical data from across your organization, including contextualized IoT data from ThingWorx.

Through powerful integration, Velotic's IIoT customers running ThingWorx on Azure, can stream IoT data via Azure Event Hubs directly into Microsoft Fabric. For a detailed guide, refer to Setting Up and Integrating ThingWorx, Azure Event Hubs, and Microsoft Fabric. Once IoT data is ingested into OneLake, it serves as a powerful foundation for advanced analytics and AI. Customers can harness Azure Machine Learning to develop predictive maintenance models or deploy Fabric Agents to act on real-time telemetry, enabling efficient data lake management, advanced analytics, and actionable insights.

In essence, ThingWorx 10.0 and Microsoft deliver a unified, edge-to-cloud solution that brings industrial data to life securely, at scale, and with AI at the core. This partnership marks a pivotal moment in industrial innovation, empowering enterprises to unlock the full potential of their data and accelerate their journey toward intelligent operations.

“Velotic brings deep industrial IoT expertise with OOTB manufacturing solutions that are easy to customize for advanced uses using the power of ThingWorx platform and Azure brings cloud-scale data management and infrastructure,” said Rabia Piacentini, Senior Partner Solution Architect, Microsoft. “Together, they simplify the journey from raw factory data to real-time, AI-driven insights.”

“We’re pleased to work with Microsoft to enhance the ThingWorx platform, whether by hosting on Azure infrastructure, using Azure Foundry LLMs for ThingWorx AI, or leveraging Azure’s data storage and management tools,” said Chris Baldwin, Vice President & General Manager, IoT at Velotic. “The combination of Velotic's platform and Azure’s capabilities supports efficient industrial innovation.”

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