Siemens Advances Smart Manufacturing Through Data and AI Collaboration

Siemens Advances Smart Manufacturing Through Data and AI Collaboration
🕧 6 min

Siemens announced a new edge-to-cloud integration with Databricks, the Data and AI company, and long‑time automation partner FFT Produktionssysteme GmbH (FFT). Together, the partners will connect production data directly to enterprise AI – without complex IoT middleware. This will help industrial customers transform their production data into actionable insights and scale industrial AI across global operations.

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With the new integration, customers are able to stream contextualized shopfloor and plant data from Siemens Industrial Edge via the FFT DataBridge directly to the Databricks Platform, where it can be analyzed and used to train AI models centrally for implementation across global production networks. These models can then be deployed back to the edge for execution at the point of production. This approach helps industrial companies optimize their operations, reduce costs and increase productivity with low‑latency, data‑driven decision‑making. It lays the foundation for physical AI and future autonomous operations.

“Industrial AI only delivers value when data, context and execution come together,” said Rainer Brehm, COO Automation and CTO at Siemens Digital Industries. “With Databricks and FFT, we enable our customers to scale industrial AI across factories and plants and make AI-powered production real.”

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Operationalizing Industrial AI with seamless IT/OT integration

With Siemens Industrial Edge and Industrial Information Hub (integration layer for industrial data), customers benefit from a secure, scalable and low-maintenance edge platform designed to unlock siloed industrial data and execute intelligent applications close to the production process. This includes advanced local analytics, physical AI and closed loop AI workflows that require low latency, high availability and strict security compliance.

Databricks complements this with advanced analytics, machine learning and agentic AI for industrial data in a cloud agnostic, governed environment with minimal infrastructure overhead. This supports a wide range of advanced use cases, including predictive maintenance, quality optimization, energy management, supply chain optimization and agentic AI applications.

“By uniting Siemens’ industrial automation and edge expertise with the Databricks Platform, we help industrial companies close the gap between industrial data and scalable business impact across their industrial network,” said Shiv Trisal, Global Industrials GTM Leader at Databricks. “This partnership is a foundational step in making human-agent collaboration a reality for industrial operations.”

Siemens Industrial Edge enables customers to deploy and manage edge devices and apps on the production site. The app ecosystem allows seamless connectivity to industrial assets, IT systems and the cloud.

FFT DataBridge: Industrialgrade data pipelines for adaptive production

FFT Produktionssysteme GmbH plays a key role in operationalizing the joint Siemens–Databricks architecture. As a long-standing Siemens partner with deep shopfloor expertise, FFT provides the DataBridge application that securely and efficiently connects Siemens Industrial Edge with the Databricks platform. FFT DataBridge streams contextualized, AI-ready production data from the edge to the cloud, where it can be combined with additional IT and OT data sources.

“Together with our partners Databricks and Siemens, FFT DataBridge provides a simple, powerful gateway to the cloud for more than 30,000 potential customers,” said Volker Stark, COO at FFT Produktionssysteme. It is ready to use and does not require expensive and time-intensive transformation of data. By natively bridging the gap between IT and OT, we eliminate the need for complex IoT layers and significantly simplify industrial connectivity for customers of Databricks.”

With the combined offering from Siemens, Databricks, and FFT, industrial producers can unlock AI‑ready production data, scale Industrial AI, and optimize operations across global production sites.

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