MUNICH – Siemens and Amazon Web Services have announced the integration of Amazon Bedrock with Mendix, the low-code platform that is part of the Siemens Xcelerator portfolio.

Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies via a single API, along with security, privacy and responsible AI capabilities.

"By integrating Amazon Bedrock into our low-code platform, we are democratizing generative AI technology and empowering everyone to create the applications customers need to become more competitive, resilient, and sustainable," said Roland Busch, CEO of Siemens. "Making smarter applications without programming expertise accelerates innovation and helps companies to tackle skilled labor shortages."

"Together, AWS and Siemens are empowering companies worldwide to create new capabilities, solutions, and value with generative AI," said Adam Selipsky, AWS CEO. "This partnership builds on our 10-year relationship with Siemens, giving customers across all industries the flexible, customizable, secure environment they need to take advantage of new opportunities with generative AI."

The combination will enable customers to select the generative AI model that best suits their specific use case and incorporate that model into their applications. Previously, when developers wanted to integrate generative AI models, they had to obtain access credentials and write specialized function code. With the new Mendix-Amazon Bedrock integration, this can now be done with just a few clicks. Teams can create smart, industry-hardened applications without dedicated programming knowledge and users can interact with information easily via a graphical interface and the simplicity of a drag and drop commands.

Mendix customers will be able apply generative AI to drive productivity within their workforce. For instance, using generative AI, a factory worker can find machine documentation faster, generating relevant visualizations without a need to manually search a database, manuals and records. A production engineer could also use generative AI to suggest machine adjustments to improve yield, and get suggestions on equipment adjustments, maintenance, or even spare parts to maximize a factory’s productivity. Customers do not need to build their own AI infrastructure and will be able to harness the power of their company’s data with the highest possible security and privacy, maintaining full control of their data.

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