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AMC Bridge Demos Requirements-to-Design AI-Assisted Compliance Automation

AMC Bridge Simulation and Digital Twin Data Interoperability and Collaboration AI and Machine Learning

Posted by Digital Engineering 24/7—AMC Bridge has developed the AI-Assisted KiCad–Codebeamer MCP Integration Demo, a technology demonstration that introduces a new approach to requirements-driven design validation and compliance automation.

The demo illustrates how AI, enabled by the Model Context Protocol (MCP), can transform disconnected engineering data into actionable, interoperable intelligence, forming a foundation for agentic AI workflows in engineering environments, AMC Bridge explains.

A new POC explores how MCP serves not only as a unifying integration layer but also as the mechanism through which AI systems can access, interpret, and act on engineering data, enabling automated requirements-driven design compliance and streamlined validation across manufacturing workflows, according to AMC Bridge.

To see the current functionality, watch a demo video.

In the demonstration view the integration of the following:

  • Codebeamer for requirements management
  • KiCad for electronic design automation (EDA)
  • Model Context Protocol (MCP) as a standard integration layer
  • An AI assistant enabling natural language interaction

This architecture transforms traditionally disconnected workflows into a cohesive, intelligent system. MCP acts as both an integration backbone and an AI access layer.

Requirements defined in Codebeamer can be automatically interpreted and validated against PCB designs created in KiCad, with AI orchestrating validation workflows and supporting user interaction through natural language.

From Static Requirements to Executable Design Constraints

Requirements act as executable constraints embedded directly within engineering workflows. The system actively:

  • Identifies noncompliance issues in real time
  • Visualizes violations within the design environment
  • Supports corrective actions immediately through natural language commands enabled by an AI assistant

The system leverages contextual knowledge from structured requirements repositories in Codebeamer® and detailed PCB design data, including layout, components, and 3D models, managed in KiCad®.

By integrating requirements management with PCB design validation, the demo enables real-time feedback on unmet requirements, automated correction, and built-in traceability—while reducing manual effort, improving design quality, and readiness for manufacturing.

The prototype also scales beyond a single PCB, supporting reuse across projects, regenerating compliant designs, and continuously revalidating results.

View the article on Digital Engineering 24/7.

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