Skip to main content

Quick Overview

Artemis is built around four modules — Build, Maintain, Discover, and Optimise — that share a single connection to your codebase. Every module reads and writes the same source of truth.

Artemis platform overview — Build, Maintain, Discover, Optimise

Getting started​

Log in to Artemis​

Access Artemis via the web platform or your local deployment. After logging in you'll land on the Projects page.

New user? Create your account here

Create a project​

From the Projects page, click + Import Project to connect a Git repository, upload a zip archive, or import a sample project. Or click Plan with AI to describe what you want to build and let the Planning Agent create a project and structured plan for you.

For detailed instructions, see Import your codebase.

Build​

The Build module helps you generate and ship code through three modes:

  • Plan — a Planning Agent breaks your goal into sub-tasks and implementation steps
  • Standalone — direct code generation tasks that apply changes automatically or via Git
  • Chat — conversational agent assistance for coding decisions, debugging, and exploration

Learn more about Build →

Maintain​

Maintain gives you a structured workflow for keeping your codebase clean and standards-compliant.

Maintain workflow — Rules → Scan → Triage → Fix

  • Rules — define quality, security, and style standards. Create rules with agent assistance, import from another project, or start from Artemis's built-in library.
  • Scan — run rules against your codebase. Select up to 20 rules per scan, set an issue budget, and watch live scan logs.
  • Triage — review findings filtered by severity. Mention #Issues and #Rules directly in chat.
  • Fix — send any issue straight to an AI coding agent. Complex issues can be escalated to Discover or a Build plan automatically.

Learn more about Maintain →

Discover​

Discover is the experimentation engine — explore objectives, generate ideas, and run experiments that produce validated code variants.

Discover experiment lifecycle

  • Objective — define what you want to improve
  • Ideas — the agent proposes candidate approaches
  • Experiments — each idea becomes an experiment that moves through Draft → Queued → In Progress → Concluded
  • Versions — each experiment produces measured code variants, scored against your metrics
  • Goals / Score — validate variants against your performance targets, then iterate

Learn more about Discover →

Optimise​

The Optimise module connects code targeting, version generation, and validation into a single pipeline:

  • Code targeting — identify areas to improve using agents, file-by-file scanning, or tool integrations
  • Version generation — generate alternatives using LLMs, agents, or Artemis Intelligence
  • Validation — verify improvements against real runtime, memory, and CPU metrics on your runner
  • Changesets — package your best versions and open a pull request directly from Artemis

Learn more about Optimise →

Agents​

All modules are powered by Artemis agents. In v3.0.0, agents are faster, more resilient, and easier to manage.

Agent capabilities — multi-tab chat and global checkpoint resume

  • Multi-tab chat — run multiple agent conversations in parallel without losing context
  • Global checkpoint resume — if an agent fails mid-run, it picks up from the last saved state automatically
  • Streaming output — responses stream directly from the LLM for noticeably faster results
  • Agents Memory — browse and query past Discovery experiments across all your projects

Learn more about Agents Memory →

Next steps​

Last updated on by Neda Zarei