You’re In! FrameworX 10.1 is Ready to Go
10.1 - Update 3a
- Full Designer environment
- All modules and features included
- 100+ connectors available
- Unlimited tags and screens
- 4-hour continuous runtime per sessions
- Unlimited restarts
.NET 8 is required to use the platform
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")
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
AI Just Built a Complete SCADA System From One Sentence
This video demonstrates how FrameworX AI Designer builds a complete industrial solution inside the live Designer IDE — tags, alarms, historian, protocols — all from a single text prompt, in real time.
What AI Designer Does:
- Connects directly to the FrameworX Designer IDE
- Creates tags, displays, alarms, and device protocols
- Configures historian and runtime settings
- Builds the entire solution from one sentence
- Shows every change in real time as it happens
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