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Overview

Artemis on AI PC enables you to run Artemis entirely on your local machine using Intel AI hardware. All AI processing, including large language models (LLMs), runs locally on your device, ensuring complete privacy and data security. This section provides comprehensive guides for installing and using Artemis on Intel AI-powered Windows machines.

What is Artemis on AI PC?​

Artemis on AI PC is a local deployment solution designed specifically for Intel AI machines running Windows OS. It leverages local GPU acceleration and on-device AI models (such as Qwen 3 4B) to provide powerful code analysis, optimization, and development assistance without sending your code to external servers.

Key Benefits​

  • Complete Privacy: All code and AI interactions remain on your local machine
  • Offline Capability: Internet access is optional; all processing runs directly on your hardware
  • High Performance: Leverages Intel GPU acceleration for fast AI processing
  • Full Control: Complete control over your development environment and data

Getting Started​

Installation​

Start by installing Artemis on your Intel AI machine using the Windows Local Installation Wizard:

  • Windows Local Installation Wizard: Step-by-step guide to install Artemis on Windows with WSL 2, Docker Desktop, and OpenVINO support. This wizard automates the entire setup process, from checking system requirements to deploying Artemis and creating your admin account.

Workflows​

Once Artemis is installed, you can use the following workflows to enhance your development process:

Code Optimization​

  • Standalone Optimisation: Improve code performance and reduce resource usage using local AI models. This workflow guides you through:
    • Importing projects and creating optimization targets
    • Scoring code blocks to identify optimization opportunities
    • Generating optimized code versions using one-shot updates or multi-version optimization with Artemis Intelligence
    • Validating and integrating optimizations into your codebase

Code Audit​

  • Code Audit: Perform comprehensive code analysis to identify security vulnerabilities, bugs, and code quality issues. This workflow covers:
    • Configuring audit rules and customizing rule importance levels
    • Running scans to identify code issues
    • Reviewing findings and prioritizing fixes
    • Automatically fixing issues using local AI assistance
    • Creating pull requests to integrate fixes

Code Exploration​

  • Agentic Chat: Explore your codebase using RAG (Retrieval-Augmented Generation) powered by local embeddings and the Qwen 3 4B model. This workflow enables you to:
    • Index your project for semantic code search
    • Ask questions about your codebase and receive answers with file references
    • Search for similar code patterns using embeddings
    • Understand code relationships and dependencies

Strategic Planning​

  • Agentic Planning: Build strategic development plans using AI assistance. This workflow helps you:
    • Create structured development plans from high-level prompts
    • Break down features into actionable sub-plans
    • Track progress and validate plan items
    • Generate code and integrate plans into your Git repository

Prerequisites​

All workflows in this section require:

  • Hardware: High-performance Intel® laptop with local GPU acceleration
  • Operating System: Windows 10 or Windows 11 with WSL 2 enabled
  • Software: Docker Desktop, latest Ubuntu Linux WSL distribution
  • AI Models: Local LLM (Qwen 3 4B model recommended)
  • Internet: Optional; all processing runs offline

Next Steps​

  1. Install Artemis: Follow the Windows Local Installation Wizard to set up Artemis on your machine
  2. Choose a Workflow: Select the workflow that matches your needs:
  3. Import Your Project: Import your codebase into Artemis to start using these workflows

Additional Resources​

Last updated on by manal