Siemens and Amazon Web Services (AWS) are strengthening their partnership and making it easier for businesses of all sizes and industries to build and scale generative artificial intelligence (AI) applications.
Domain experts in fields such as engineering and manufacturing, as well as logistics, insurance or banking will be able to create new and upgrade existing applications with the most advanced generative AI technology. To make this possible, 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, the leading low-code platform that is part of the Siemens Xcelerator portfolio.
The combination will enable customers to select the generative AI model that best suits their specific use case and quickly and securely 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.
This innovation allows Mendix customers to 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 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.
Generative AI technology can supercharge applications with features like summarizing and analyzing lengthy technical or legal documents, translating content into different languages or recognizing images. Financial businesses can integrate automatic fraud detection in their software, while workers in a car factory can improve quality based on AI analysis of millions of data points in the manufacturing line.
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.
Today, more than 50 million end users 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 industry-leading 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 customized responses.
The Mendix-Amazon Bedrock integration complements AWS’ 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.
