DEVOPSdigest

Mendix outlined new AI and machine learning capabilities, including innovative context-aware AI developer tools, which will all be available upon the release of Mendix 10.

The new AI and Machine Learning enhancements reinforce the status of Mendix's low-code platform as the de facto standard for building smart business applications and solutions. Mendix 10 features greatly expanded AI capabilities in two major areas. First, Mendix 10 empowers the enterprise to seamlessly integrate AI use cases with low-code applications using Mendix's new Machine Learning Kit. Secondly, the platform greatly expands the scope and functionality of AI-enabled application development.

Mendix 10 features a new Machine Learning (ML) Kit that empowers enterprises to build solutions incorporating custom AI models within applications using the developer's desired AI framework and language. These include pretrained models built with PyTorch, Caffee2, Cognitive Toolkit, and other common AI frameworks that have adopted the Open Neural Network Exchange (ONNX) standard. ONNX-based models can be easily imported into Mendix's integrated development environment (IDE) and weaved into a Mendix application. In doing so, this offers support for various inference patterns, and pre- and post-processing logic. The Mendix runtime has been enhanced to support seamless execution of ONNX-based models, enabling the ML model to run in the same environment as the application.

The ease of packaging and deploying these pre-trained models — whether open sourced or developed internally — within Mendix applications brings the low-code experience of speed, scalability, superior UI, and accelerated time-to-market to enterprises seeking to harness AI technology for business value and ROI.

By eliminating time-consuming tasks of manual integration, the ML Kit can reduce AI deployments from weeks to hours. The lower latency of the built-in integration of embedded AI models versus API-based integration drives the superior performance of AI-enhanced applications as the ML model runs in the same container as the application. Also, embedded AI model deployment enables the robust continuity of AI services when used offline, on-edge, or in IoT uses. Finally, in-application deployment of ML models eliminates the need to upload enterprise data or IP to third-party systems outside of the Mendix application landscape, thus providing another layer of security.

The Mendix ML Kit is based on Open Neural Network Exchange (ONNX), an open-source framework created in 2017 to enable framework interoperability. ML Kit provides access to dozens of pre-trained, out-of-the-box machine language models from the ONNX Model Zoo that are fully customizable.

"Enterprises with sophisticated machine learning capabilities can easily incorporate their models into Mendix applications using the ML Kit," said Amir Piltan, Mendix's senior product manager for AI. "But for those earlier in the adoption curve, it is not necessary for enterprises to build models from scratch. They can start with the ONNX Model Zoo, fine-tune the model for specific use cases, and keep their data and AI model secure, as it never leaves their Mendix ecosystem. This makes AI deployment easier from an operational, commercial, and governance standpoint."

A second area of enhancements targeting developers features the new Mendix Assist Best Practice bot that provides a virtual AI-enabled "co-developer" that inspects applications in real-time to implement Mendix software development best practices. The Data Validation bot helps developers build validation logic in an automated way using pre-built expressions. These platform upgrades to the Mendix Assist bot family put the power of software development into the hands of a broad spectrum of developers, e.g. enabling business technologists to create solutions with AI assistance to ensure the highest level of quality.

Mendix's new bots also serve as valuable resources for skilled developers, helping to ensure that their applications conform to Mendix development best practices by identifying development anti-patterns, providing their location, and guiding developers on how to address and resolve them.

At their core, the new AI-driven bots are designed to boost the productivity and efficiency for Mendix developers across a range of skill sets while optimizing the performance and quality of Mendix applications.

"We believe AI tools and low-code development are a natural fit to build better software faster," said Hans de Visser, Mendix's chief product officer. "Enterprises using low-code will be able to extract more value from AI in an efficient way using the new features of the Mendix 10 platform."

De Visser added, "Our next step will be the introduction of "Mendix Chat," a chat bot in the Mendix IDE that will guide developers on how to apply certain concepts or patterns. We are currently training a large language model based on sources drawn from Mendix Forum, Mendix documentation, and our support system. Next, we will bring generative AI into our DSLs and generate models and model elements based on natural language input. This means app developers and business domain experts will be able to use free text — a user story — and from that, generate application models."

"We have applied the core principles of low-code abstraction and automation for customers seeking a connected landscape to embed their machine language models into an application," said Amir Piltan, Mendix's senior product manager for AI. "Mendix is the first platform that enables developers to easily drag and drop ML models into the application's logic and deploy it without the need to use an outside service."

Piltan adds, "The combined use of Mendix Assist bots and the ML Kit will boost developer productivity across the entire lifecycle of software development, enabling them to build smart apps in a smart way. With Mendix 10, enterprises are empowered to meet ever-changing market demands and deliver innovation quickly."