You’re In! FrameworX 10.1 is Ready to Go
10.1
- Full Designer environment
- All modules and features included
- 100+ connectors available
- Unlimited tags and screens
- 4-hour continuous runtime per sessions
- Unlimited restarts
Important
If you’ve installed a previous version using MSIX, please uninstall it first to prevent conflicts. Removing the prior installation also speeds up the setup process by avoiding incremental updates that take longer to verify and replace files. Additionally, make sure to stop any running instances of the application and remove any Windows Services associated with it before proceeding.
Build Faster with a Tatsoft Engineer
Our Tatsoft Assistance Team team is here to help you:
- Solve a specific application challenge
- Set up your first tags, displays, and data sources
- Review the best way to deploy FrameworX in your environment
- Learn how to get the most out of scripting, WebAssembly graphics, or MQTT
To create solutions to other operating platforms like Linux or web pages, .NET 8 is required.
If you receive a warning that .NET 8 is not available on your computer, it will not prevent you from configuring solutions targeting Windows only, but it will prevent multi-platform solutions or the deployment of web pages.
To install the .NET 8, follow the link in the installer message, or you can find the .NET 8 Desktop Runtime installer from Microsoft here: https://dotnet.microsoft.com/en-us/download/dotnet/8.0. Be sure to pick the version that matches your CPU architecture, which is likely x64. (And don’t pick the “SDK” or “.NET Runtime” or other versions – just the “.NET 8 Desktop Runtime“)
From MQTT Data to Machine Learning: Bottling Line Demo
This guide demonstrates how to create a complete IoT solution that collects data from the field, publishes it to an MQTT broker, historizes the data, applies machine learning models, and displays real-time values.
System Overview:
- Collects data from field devices (simulated)
- Publishes data to MQTT broker
- Historizes data to SQLite database
- Applies machine learning models to monitor anomalies
- Displays real-time values in customizable dashboards
Real-Time SCADA Meets AI: FrameworX 10.1 Solar Panels Demo
This guide demonstrates how to integrate MQTT Tools with Cloud AI by setting up a Built-in Broker, mapping MQTT data to the solution namespace, creating assets, and configuring MCP scripts for solar panel monitoring.
System Overview: Your solution now:
- Runs a Built-in MQTT Broker with SparkPlug simulation
- Maps MQTT data structure to the solution namespace
- Organizes data through the Europe asset structure
- Monitors solar panel data via MCP scripts
- Provides intelligent insights through Cloud AI integration
- Enables real-time queries and analysis of MQTT data