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FrameworX provides practical AI capabilities for industrial automation.
Platform Overview | AI Integration
Why AI Integration Matters
Engineers using AI copilot tools with FrameworX report productivity improvements of 2× to 10× for configuration tasks, depending on complexity. This isn't a marginal improvement; it's a fundamental change in how industrial applications are built.
FrameworX provides practical AI integration across three areas: design-time assistance, runtime queries, and machine learning deployment.
→ For the technical architecture that enables this, see AI-Ready by DesignThe Next Frontier: A decade ago, the industry focused on OT-IT integration. Now the frontier is OT-AI integration. The same architectural decisions that enabled OT-IT — consistent namespaces, managed code, open interfaces — now enable native AI integration.
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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 manage the Designer UI. |
| 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 |
| Ask FrameworX Docs | ChatGPT trained on documentation | Get help, ask questions. side bar shortcut: AI Ask Docs | 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
| Info |
|---|
Additional to ML in C#, the Python 3 native integration allows the usage of all Python analytics libraries. |
→ See AI ML Integration Connector
→ See Python .NET Integration
Ask FrameworX Docs
ChatGPTin getting trained on FrameworX documentation.
You can click here → AI Ask Docs, or use the shortcut on left top sidebar.
Reference Link
→ For the technical architecture that enables this, see AI-Ready by Design