Artemis Documentation
Artemis is an AI-powered code intelligence platform that helps engineering teams build, maintain, discover, and optimise their codebases — through intelligent agents, real execution metrics, and a unified multi-module workflow.
The four modules
Build
Plan tasks, generate code, and run agentic development workflows from natural language. Includes Plan mode for structured strategies, Standalone tasks for direct code changes, and Chat for conversational assistance.
Maintain
Define quality rules, scan your codebase for violations, triage findings by severity, and fix them directly with an AI coding agent. Rules can be created, imported, or seeded from Artemis's built-in library.
Discover
Explore objectives, generate ideas and experiments, and track code variants through their full lifecycle — from draft to validated. A rebuilt ground-up experience in v3.0.0 with multi-LLM review, multi-metric plots, and a unified experiment board.
Optimise
Target specific code, generate improved versions, validate against real execution metrics, and ship regression-safe changes. Connects directly to Discover experiments and produces changesets you can open as pull requests.
Agents
Artemis agents power all four modules. In v3.0.0 they got significantly faster and more resilient:
- Streaming from the LLM — noticeably faster output for long responses
- Global checkpoint resume — if an agent fails mid-run, it recovers from the last good state
- Multi-tab chat — run multiple agent conversations in parallel tabs
- Agents Memory — browse past Discovery experiments across all projects and ask questions about them
Get started
- Quick Overview — the full Artemis workflow in one page
- Sign up / Log in — create your account
- Import your codebase — connect a repository or start from scratch
- Git Keys — authenticate with your git provider
Platform & settings
- Platform Settings — agent limits, contexts, model management, MCP servers
- Admin Settings — per-user governance, usage tracking, feature flags
- Custom Runner — run builds and benchmarks on your own hardware
- Artemis CLI — manage projects and tasks from the terminal
- MCP Servers — connect external data sources to your agents
- Agents Memory — search and query past experiments across all projects
Deployment & architecture
- Deployment Options — SaaS or on-premise
- Architecture Overview — how Artemis works under the hood
- Release Notes — what's new in v3.0.0
Need help?
- FAQs
- Email: support@turintech.ai