Domain experts in fields such as engineering and manufacturing, as well as logistics, insurance or banking will now be able to create new and upgrade existing applications with the most advanced generative AI technology.
Siemens is integrating Amazon Bedrock - a service that offers a choice of high-performing foundation models from leading AI companies via a single API, along with security, privacy, and responsible AI capabilities - with Mendix, thelow-code platform that is part of the Siemens Xcelerator portfolio.
“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 labour shortages.”
“Together, AWS and Siemens are empowering companies worldwide to create new capabilities, solutions, and value with generative AI,” added Adam Selipsky, AWS CEO. “This partnership builds on our 10-year relationship with Siemens, giving customers across all industries the flexible, customisable, secure environment they need to take advantage of new opportunities with generative AI.”
Customers will be able to select the generative AI model that best suits their specific use case and then incorporate that model into their applications. This will make their development simpler, faster, and more efficient. 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 in just a matter of a few clicks.
Teams will be able to 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.
This innovation allows Mendix customers to apply generative AI to drive productivity within their workforce.
For example, a production engineer could 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.
According to Siemens, customers do not need to build their own AI infrastructure and will be able to use their company’s own data with the highest possible security and privacy, maintaining full control of their data.
The collaboration expands on the long-established partnership between AWS and Siemens to help streamline the use of IT and cloud technology so it can be easily integrated in applications and machine workflows, making it seamless to engage with.
At present some 50 million end users around the worldwide work with more than 200,000 applications built with Mendix’s low-code platform, available as part of the Siemens Xcelerator portfolio. Low-code platforms are expected to grow substantially over the next years. The technology enables developers to create applications by drag and drop with reusable components and software building blocks, which means they can build more software faster and with smaller teams.
Amazon Bedrock is a fully managed service that offers easy access to a choice of large language models and other foundation models from AI21 Labs, Amazon, Anthropic, Cohere, Meta, and Stability AI, along with a broad set of capabilities that customers need to build generative AI applications—simplifying development while supporting privacy and security.
Users can also apply Guardrails to filter undesired content, adhere to responsible AI policies, or finetune their models using Knowledge Bases for Amazon Bedrock to give contextual information from private data sources and more relevant, accurate, and customised responses.
The Mendix-Amazon Bedrock integration complements AWS’s other generative AI services, like Amazon CodeWhisperer, a machine learning (ML)-powered service that helps improve developer productivity by generating code recommendations based on developers’ comments in natural language and their code.
