Enrich Your Mendix App with GenAI Capabilities

Last modified: January 17, 2025

Introduction

With the Mendix GenAI capabilities, you can create engaging, intelligent experiences with a variety of AI models and your own data.

Typical Use Cases

Mendix supports a variety of generative AI tasks by integrating with tools such as Amazon Bedrock or Azure OpenAI. 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:

  1. Familiarize yourself with the concepts such as prompt engineering, Retrieval Augmented Generation (RAG), and function calling (ReAct).
  2. Select the right architecture to support your use case. For a full list of possibilities, see the Architecture and Components section below.
  3. Obtain the required credentials for your selected architecture.

Architecture and Components

To help you get started, the following sections list the available GenAI components and models.

Mendix Components

Asset Description Type Studio Pro Version
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 10.12
Blank GenAI App Start from scratch to create a new application with GenAI capabilities and without any dependencies. Starter App 10.12
GenAI Showcase App Understand what you can build with generative AI. Understand how to implement the OpenAI and Amazon Bedrock connectors and how to integrate them with the Conversational UI module. Showcase App 9.24.2
RFP Assistant Starter App / Questionnaire Assistant Starter App The RFP Assistant Starter App and the Questionnaire Assistant Starter App leverage historical RFPs (or question-answer pairs) and a continuously updated knowledge base to generate and assist in editing responses to RFPs, offering a time-saving alternative to manually finding similar responses and enhancing the knowledge management process. Starter App 9.24.2
Support Assistant Starter App Learn how to combine common GenAI patterns, such as function calling and RAG to build your support assistant. Connect it to a model like Anthropic Claude or Amazon Titan via Amazon Bedrock or use an (Azure) OpenAI subscription. Starter App 10.12
Conversational UI Create a Conversational UI for a new or existing app. UI Module 9.24.2
OpenAI Connector Connect to Azure OpenAI. Connector Module 9.24.2
Amazon Bedrock Connector Connect to Amazon Bedrock. Use Retrieve & Generate or Bedrock agents. Connector Module 9.24.2
PgVector Knowledge Base Manage and interact with a PostgreSQL pgvector Knowledge Base. Connector Module 9.24.2
GenAI Commons Common capabilities that allow all GenAI connectors to be integrated with the other modules. You can also implement your connector based on this. Common Module 9.24.2
Snowflake Showcase App Learn how to implement the Cortex functionalities in your app. Showcase App 10.12

Available Models

Mendix connectors offer direct support for the following models:

Architecture Models Category Input Output Additional capabilities
Azure / OpenAI gpt-3.5-turbo Chat completions text text Function calling
gpt-4, gpt-4-turbo, gpt-4o, gpt-4o mini Chat completions text, image text Function calling
DALL·E 2, DALL·E 3 Image generation text image
text-embedding-ada-002, text-embedding-3-small, text-embedding-3-large Embeddings text embeddings
Amazon Bedrock Amazon Titan Text G1 - Express, Amazon Titan Text G1 - Lite, Amazon Titan Text G1 - Premier Chat Completions text text Document Chat (except Titan Premier)
AI21 Jamba-Instruct Chat Completions text text
AI21 Labs Jurassic-2 (Text) Chat Completions text text
Amazon Nova Pro, Amazon Nova Lite Chat Completion text text Function calling, Document Chat
Amazon Titan Image Generator G1 Image generation text image
Amazon Titan Embeddings Text v2 Embeddings text embeddings
Anthropic Claude v2.0, Anthropic Claude v2.1 Chat Completions text text Document Chat
Anthropic Claude v3 Sonnet, Anthropic Claude v3 Haiku, Anthropic Claude v3 Opus Chat Completions text, image text Function calling, Document Chat
Anthropic Claude v3.5 Sonnet, Anthropic Claude v3.5 Sonnet v2 Chat Completions text, image text Function calling, Document Chat
Cohere Command Chat Completions text text Document Chat
Cohere Command Light Chat Completions text text
Cohere Command R, Cohere Command R+ Chat Completions text text Function calling, Document Chat
Cohere Embed English, Cohere Embed Multilingual Embeddings text embeddings
Meta Llama 2, MetaLlama 3 Chat Completions text text Document Chat
Meta Llama 3.1 Chat Completions text text Function calling, Document Chat
Mistral AI Instruct Chat Completions text text Document Chat
Mistral Large, Mistral Large 2 Chat Completions text text Function calling, Document Chat
Mistral Small Chat Completions text text Function calling
Mendix Cloud GenAI Anthropic Claude v3.5 Sonnet Chat Completions text, image text Function calling, Document Chat
Cohere Embed English, Cohere Embed Multilingual Embeddings text embeddings

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: