Enrich Your Mendix App with GenAI Capabilities
Last modified: January 22, 2026
Introduction
With the Mendix GenAI capabilities, you can create engaging, intelligent experiences with a variety of AI models and your own data.
These pages cover modules that integrate with generative AI tools. For running pre-trained Machine Learning (ML) models using the Mendix Runtime, please see the Machine Learning Kit.
Typical Use Cases
Mendix supports a variety of generative AI tasks by integrating with tools such as Amazon Bedrock or Microsoft Foundry. Typical use cases include the following:
- Create conversational UIs for AI-powered chatbots and integrate those UIs into your Mendix applications.
- Connect any model through our GenAI connectors, or by integrating your connector into our GenAI commons interface.
- Connect your data to ground GenAI systems with data from inside your application and the rest of your IT landscape.
Getting Started
To familiarize yourself with the GenAI capabilities of Mendix, explore the sections below based on your experience level:
Familiar with GenAI
If you are already familiar with GenAI and want to start building, refer to How to Build Smarter Apps Using GenAI guide to start building your first GenAI-powered application and access further supportive resources.
New to GenAI
If you are new to GenAI, follow the steps below:
- Familiarize yourself with the concepts such as prompt engineering, Retrieval Augmented Generation (RAG), and function calling (ReAct).
- Select the right architecture to support your use case. For a full list of possibilities, see the Architecture and Components section below.
- Obtain the required credentials for your selected architecture.
Architecture and Components
Supercharge your applications with Mendix's Agents Kit. This powerful set of components puts cutting-edge GenAI capabilities at your fingertips, helping you make your Mendix apps smarter. Explore our collection of components and models as listed on this page. Please note that the toolkit supports the full spectrum of generative AI implementations, from straightforward text generation to complex agentic AI.
Mendix Components
| Asset | Description | Type | Studio Pro Version |
|---|---|---|---|
| Agent Builder Starter App (formerly known as Support Assistant Starter App) | See an example of how to build an agentic Mendix application. Use the Agent Builder from Agent Commons to build your support assistant. | Starter App | 10.24 |
| Agent Commons | Build agentic functionality using common patterns in your application by defining, testing, and evaluating agents at runtime. | Common Module | 10.24 |
| AI Bot Starter App | Lets you kick-start the development of enterprise-grade AI chatbot experiences. For example, you can use it to create your own private enterprise-ready ChatGPT-like app. | Starter App | 10.24 |
| Amazon Bedrock Connector | Connect to Amazon Bedrock. Use Retrieve and Generate or Bedrock agents. | Connector Module | 10.24 |
| Blank GenAI App | Start from scratch to create a new application with GenAI capabilities and without any dependencies. | Starter App | 10.24 |
| Conversational UI | Create a Conversational UI or monitor token consumption in your app. | UI Module | 10.24 |
| GenAI Commons | Common capabilities that allow all GenAI connectors to be integrated with the other modules. You can also implement your own connector based on this. | Common Module | 10.24 |
| GenAI Showcase App | Understand what you can build with generative AI. Understand how to implement the Mendix Cloud GenAI, OpenAI, and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. | Showcase App | 10.24 |
| MCP Client | Access tools and prompts available via MCP (Model Context Protocol) inside of your Mendix app and add them to LLM requests. | Connector Module | 10.24 |
| MCP Server | Make your Mendix business logic available to any agent in your enterprise landscape with the Mendix MCP Server module. Expose reusable prompts, including the ability to use prompt parameters. List and run actions implemented in the application as a tool. | Module | 10.24 |
| Mendix Cloud GenAI Connector | Connect to Mendix Cloud and utilize Mendix Cloud GenAI resource packs directly within your Mendix application. | Connector Module | 10.24 |
| Mistral Connector | Connect to Mistral AI. | Connector Module | 10.24 |
| OpenAI Connector | Connect to OpenAI and Microsoft Foundry. | Connector Module | 10.24 |
| PgVector Knowledge Base | Manage and interact with a PostgreSQL pgvector Knowledge Base. | Connector Module | 10.24 |
| RFP Assistant Starter App / Questionnaire Assistant Starter App | The RFP Assistant Starter App and the Questionnaire Assistant Starter App leverage historical question-answer pairs (RFPs) and a continuously updated knowledge base to generate and assist in editing responses to RFPs. This offers a time-saving alternative to manually finding similar responses and enhancing the knowledge management process. | Starter App | 10.24 |
| Snowflake Showcase App | Learn how to implement the Cortex functionalities in your app. | Showcase App | 10.24 |
Older versions of the marketplace modules and GenAI Showcase App are available in Studio Pro 9.24.2.
Available Models
Mendix connectors offer direct support for the following models:
| Architecture | Models | Category | Input | Output | Additional capabilities |
|---|---|---|---|---|---|
| Mendix Cloud GenAI | Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4.0 Sonnet, Anthropic Claude 4.5 Sonnet | Chat Completions | text, image, document | text | Function calling |
| Cohere Embed v3 English and multilangual, Cohere Embed v4 | Embeddings | text | embeddings | ||
| Microsoft Foundry (OpenAI) / OpenAI | gpt-4, gpt-4-turbo, gpt-4o, gpt-4o mini, gpt-4.1, gpt-4.1-mini, gpt-4.1-nano, gpt-5.0, gpt-5.0-mini, gpt-5.0-nano, gpt-5.1, gpt-5.2, o1, o1-mini, o3, o3-mini, o4-mini | Chat completions | text, image, document (OpenAI only) | text | Function calling |
| DALL·E 2, DALL·E 3, gpt-image-1 | Image generation | text | image | ||
| text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large | Embeddings | text | embeddings | ||
| Mistral | Mistral Large 3, Mistral Medium 3.1, Mistral Small 3.2, Ministral 3 (3B, 8B, 14B), Magistral (Small, Medium) | Chat Completions | text, image | text | Function calling |
| Codestral, Devstral (Small, Medium), Open Mistral 7B, Mistral Nemo 12B | Chat Completions | text | text | Function calling | |
| Mistral Embed, Codestral Embed | Embeddings | text | embeddings | ||
| Amazon Bedrock | Amazon Titan Text G1 - Express, Amazon Titan Text G1 - Lite, Amazon Titan Text G1 - Premier | Chat Completions | text, document (except Titan Premier) | text | |
| AI21 Jamba-Instruct | Chat Completions | text | text | ||
| AI21 Labs Jurassic-2 (Text) | Chat Completions | text | text | ||
| Amazon Nova Pro, Amazon Nova Lite | Chat Completions | text, image, document | text | Function calling | |
| Amazon Titan Image Generator G1 | Image generation | text | image | ||
| Amazon Titan Embeddings Text v2 | Embeddings | text | embeddings | ||
| Anthropic Claude 3 Sonnet, Anthropic Claude 3.5 Sonnet, Anthropic Claude 3.5 Sonnet v2, Anthropic Claude 3 Haiku, Anthropic Claude 3 Opus, Anthropic Claude 3.5 Haiku, Anthropic Claude 3.7 Sonnet, Anthropic Claude 4.5 Sonnet, Anthropic Claude 4.5 Haiku, Anthropic Claude 4.5 Opus | Chat Completions | text, image, document | text | Function calling | |
| Cohere Command | Chat Completions | text, document | text | ||
| Cohere Command Light | Chat Completions | text | text | ||
| Cohere Command R, Cohere Command R+ | Chat Completions | text, document | text | Function calling | |
| Cohere Embed English, Cohere Embed Multilingual | Embeddings | text | embeddings | ||
| DeepSeek, DeepSeek-R1 | Text | text | document | ||
| Meta Llama 2, MetaLlama 3 | Chat Completions | text, document | text | ||
| Meta Llama 3.1 | Chat Completions | text, document | text | Function calling | |
| Mistral AI Instruct | Chat Completions | text, document | text | ||
| Mistral Large, Mistral Large 2 | Chat Completions | text, document | text | Function calling | |
| Mistral Small | Chat Completions | text | text | Function calling | |
| OpenAI gpt-oss-20B, gpt-oss-120b | Chat Completions | text | text |
For more details on limitations and supported model capabilities for the Bedrock Converse API used in the ChatCompletions operations, see Supported models and model features in the AWS documentation.
The available showcase applications offer implementation inspiration for many of the listed models.
Connecting to Other Models
In addition to the models listed above, you can also connect to other models by implementing one of the following options:
- To connect to other foundation models and implement them in your app, use the Amazon Bedrock connector.
- To connect to Snowflake Cortex LLM functions, configure the Snowflake REST SQL connector for Snowflake Cortex Analyst.
- To implement your connector compatible with the other components, use the GenAI Commons interface and follow the how-to Build Your Own GenAI Connector.