simaticai 2.8.0

AI Software Development Kit

AI Software Development Kit

Siemens AG - Industrial AI Suite

Streamline Industrial AI Development and Deployment

The AI Software Development Kit (the simaticai Python Package) is a comprehensive Python library designed to simplify the creation, packaging, and testing of AI inference pipelines for the Industrial AI Suite. Part of Siemens' Industrial Edge ecosystem, this SDK accelerates the integration of AI solutions into manufacturing environments.

Key Features

• Complete ML Pipeline Support: Create and package AI inference pipelines with ease
• Notebook-Based Tutorials: Ready-to-use End to End Tutorials for model training and deployment
• Industrial Edge Integration: Seamless connectivity with SIMATIC and Industrial Edge infrastructure
• Cloud Compatibility: Native integration with leading cloud-based ML environments (such as Microsoft Azure)
  
• GPU Acceleration: Optimized for NVIDIA GPU-powered Industrial PCs
• Production-Ready: Built for industrial-grade reliability and performance

Quick Links

Documentation & Resources

• Industrial AI Suite Overview
  
• Developer Documentation
  
• AI SDK Tutorials
  
• Microsoft Azure Reference Architecture

Support

• Enterprise-grade Siemens support
  
• Industrial Edge ecosystem backing
  
• Regular updates and security patches
  
• Technical consultation available
  
• Website: https://support.industry.siemens.com/

Quick Start

The code examples only represent the main steps to create an AI Inference Pipeline using Package simaticai, to enjoy the full experience, please study the public tutorials or discover the code repository on Github.

Create an AI inference pipeline

from simaticai.deployment import PythonComponent, Pipeline
# creating a Pipeline Step for classification
classification = PythonComponent(name="classification")  

# [..] additional steps to add resources and defining the environment

# creating of the Pipeline
pipeline = Pipeline("Image Classification")  
# adding the classification step
pipeline.add_component(classification)  

# [..] final steps to define the Pipeline properties and behavior

Package for deployment

# saving the Pipeline for deployment
package_path = pipeline.export("./deploy")

Prerequisites

• Python >=3.10
• pip >= 21.3.1 (automatically upgraded during installation)
• Compatible with Industrial Edge devices
• NVIDIA GPU support (recommended)

Why choose AI SDK?

🏭 Bridge the gap between AI development and shop floor deployment
🚀 Accelerate time-to-value for industrial AI solutions
🔄 Streamline ML operations across multiple locations
🛠️ User-friendly tools for automation engineers
🔌 Native integration with SIMATIC and Industrial Edge ecosystem
☁️ Cloud-ready architecture

Part of Industrial AI Suite

This SDK is a core component of the Industrial AI Suite, which provides:

• Seamless cloud integration
  
• Complete MLOps infrastructure
  
• Multi-location model scaling
  
• Industrial Edge ecosystem integration
  
• User-friendly deployment tools
  
• Production monitoring capabilities
  

Benefits

For Data Scientists

• Focus on model development while we handle deployment
  
• Familiar notebook-based workflows
  
• Seamless integration with existing ML tools
  
• Support for most used frameworks and multiple libraries
  

For Automation Engineers

• No prior data science experience required
  
• User-friendly deployment interfaces
  
• Integrated monitoring solutions
  

For Operations

• Scale AI solutions across locations
  
• Reliable industrial-grade performance
  
• Fast return on investment
  

License

MIT license - Contact Siemens for licensing options