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FrameworX provides practical AI capabilities for industrial automation.
Platform Overview | AI Integration
AI Capabilities Overview
| Capability | What It Does | Use For | Unique Features |
|---|---|---|---|
| MCP for Runtime | AI models query live solution data | Dashboards, troubleshooting, automated reports | Easily creates custom MCP runtime tools to each solution |
| MCP for Designer | AI models help build solutions | Faster configuration, bulk object creation | AI Tools (Claude, Copilot) directly manages manage the Designer UI. All solution elements can be created, and the user has visual feedback on what and how they are created 17 tools for creating all solution elements with visual feedback. |
| ML Integration | Deploy trained ML models | Anomaly detection, predictive maintenance | Use directly ML NET 4.0 in C# User directly all Python 3.7+ libraries |
| FrameworX AI Assistant | ChatGPT trained on documentation | Get help, ask questions | Leverage OpenAI tools |
MCP for Runtime — Query Live Data
Connect AI models like Claude to your running solution.
What AI can do:
- Read tag values from the UNS
- Query alarms and historian
- Create custom queries via Script Classes
→ See AI MCP for Runtime Connector
MCP for Designer — AI-Assisted Configuration
Let AI help you build solutions faster with 17 specialized tools.
What AI can do:
- Create Tags, Displays, Alarms, Devices, and all solution objects
- Generate
- Canvas and Dashboard displays with proper patterns
- Search protocols by equipment name (Siemens, Allen-Bradley, Modbus)
- Track changes, cross-references, and audit trails
- Access documentation and download example solutions
Key Features:
- MCP Category System — Tracks AI-created vs manually-created objects
- Wizard Symbols — Pre-built industrial symbols (BLOWER, MOTOR, PUMP, TANK, VALVE)
- Protocol Search — Fuzzy matching finds protocols by vendor name
- Visual Feedback — Designer UI shows changes as they happen
→ See AI MCP for Designer Connector
ML.NET Integration — Deterministic Machine Learning
Deploy trained models for consistent, repeatable results.
Use cases:
- Anomaly detection
- Predictive maintenance
- Quality prediction
→ See AI ML Integration Connector
FrameworX AI Assistant
ChatGPTin getting trained on FrameworX documentation. (Preview Feature)
Learn More
→ AI-Ready by Design — Deep dive into the technical architecture → AI MCP for Runtime Tutorial → AI MCP for Designer Tutorial