Artemis Documentation
Artemis is a code optimisation platform. You give it a codebase, an Objective, a representative benchmark and the checks a change must pass. Artemis generates candidate changes, runs experiments on hardware you control, compares the results with the Baseline, and returns the improvements as reviewable code changes with their evidence. You can use it in the browser, from the Artemis CLI, or from a coding agent such as Claude Code.
Inside a Project
The Project sidebar follows the work: Overview, AI Agents, then the workflows Maintain, Discover and Plan, then the code in Branches and Files, and finally Project Settings.
Maintain
Define Rules, scan your code for Issues, triage the findings, and fix them with a coding agent, in a Discovery Run, or with your own local agent. Rules can be written in Markdown, drafted with the Maintain agent, copied from another Project or taken from the Rule Library.
Discover
Run a Discovery: Artemis explores many candidate changes toward an Objective with several models, measures each Version against the Baseline on your Runner, and keeps the evidence for every Experiment. Without a Runner, a panel of judge models scores the Versions instead, for work such as improving a written Plan.
Plan
Break a piece of work into Tasks before any code is written, then build the Plan on a new Branch.
Branches
Review, verify and publish proposed code changes. Every coding agent works on its own Branch, and nothing reaches your Git provider until you publish it.
AI Agents
Start a chat, a Plan, a Maintain agent or a Discovery Run, and follow every agent working on the Project from one page.
Get started
- Quick Overview: the full Artemis workflow in one page
- Videos: short explanations of Runners, benchmarks, Discovery, Maintain and using Artemis with a coding agent
- Sign up / Log in: create your account
- Import your codebase: connect a repository or start from scratch
- Git Integration: authenticate with your Git provider
Platform and settings
- Platform Settings: Skills, agent limits, Git, Runners, API keys and MCP connections
- Admin Settings: AI models, users, logs and feature flags
- Artemis Runner: run builds and benchmarks on your own hardware
- Artemis CLI: drive Artemis from the terminal or a coding agent
- MCP Connections: give your agents tools from external services
- Agents Memory: the past Experiments agents recall across your Projects
Deployment and architecture
- Deployment Options: SaaS or on-premise
- Architecture Overview: how Artemis works under the hood
- Release Notes
Need help?
- FAQs
- Email: support@turintech.ai