An AI tool helps automation engineers write code, configure systems, connect electrical designs, and build engineering projects.
Siemens has launched the Eigen Engineering Agent, giving automation engineers access to an industrial AI system that can plan, execute, and validate engineering tasks within TIA Portal. The agent is designed to go beyond providing recommendations by carrying out tasks such as PLC programming, HMI visualisation, device configuration, and project generation.
Unlike conventional AI assistants that generate suggestions for engineers to implement, the Eigen Engineering Agent works directly with the engineering project. It analyses the project structure, creates or modifies control software, configures systems, checks the results, and continues refining its output against defined quality requirements.
The agent is integrated with TIA Portal, Siemens’ engineering software platform, and is part of the Siemens Xcelerator portfolio. Its direct connection to the engineering environment gives it access to project data, blocks, parameters, and relationships between components. This allows it to generate outputs based on the actual system being engineered, including projects where documentation may be incomplete or outdated.
One is ECAD integration, which allows the agent to work with electrical design files in formats such as XML and AML. It can identify inconsistencies, resolve or flag issues, add devices to a TIA Portal project, configure connections, and generate PLC tags based on the hardware topology. This connects electrical design information with the subsequent automation programming workflow.
The second is standards-compliant project generation. Engineers can describe a machine, its stations, devices, and required behaviour in natural language. The agent can then generate a complete project structured according to the Siemens Automation Framework, providing a starting point that can be opened and developed further in TIA Portal.
According to the company, users have recorded two to five times faster execution compared with manual workflows, up to 50% higher engineering efficiency, and an 80% improvement in overall solution quality. In one automotive line-building application, new engineers were able to query the project directly instead of spending weeks learning its structure, reducing onboarding time from weeks to days.
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