> For the complete documentation index, see [llms.txt](https://docs.bito.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bito.ai/quickstart.md). # Quickstart This guide will help you set up and start using Bito's AI-powered tools. Whether you're looking to enhance feedback of your coding agents with [AI Architect](/ai-architect/overview.md) or automate code reviews with our [AI Code Review Agent](/ai-code-reviews-in-git/overview.md), you'll find everything you need below. ### AI Architect {% stepper %} {% step %} ### Prerequisites [Bito's AI Architect](/ai-architect/overview.md) is currently invitation-only. To request access, contact . {% endstep %} {% step %} ### Install AI Architect Bito offers two deployment options for AI Architect. * [**Bito-hosted**](/ai-architect/installation/install-ai-architect-bito-hosted.md) (Fully managed by Bito — no infrastructure setup required) * [**Self-hosted**](/ai-architect/installation/install-ai-architect-self-hosted.md) (Run AI Architect on your own infrastructure for maximum control) #### Bito-hosted 1. [Log in to Bito Cloud](https://alpha.bito.ai/) and connect your Git provider. 2. From the [Home](https://alpha.bito.ai/home) screen, click **Configure** next to **Set up AI Architect**, then select the repositories you want indexed. 3. Bito indexes your repositories, builds the underlying knowledge graph, and notifies you once your indexes are ready. [**Guide for Bito-hosted AI Architect →**](/ai-architect/installation/install-ai-architect-bito-hosted.md) #### Self-hosted 1. Download and install AI Architect with a single command. ```shellscript curl -fsSL https://aiarchitect.bito.ai/install.sh | bash ``` 2. Configure AI Architect with your Git and LLM credentials. 3. Configure your repositories 4. Start indexing to build knowledge graph of your codebase 5. Get your MCP server URL and access token [**Guide for self-hosted AI Architect →**](/ai-architect/installation/install-ai-architect-self-hosted.md) {% endstep %} {% step %} ### Connect Bito's AI Architect with your tools AI Architect integrates with the tools you already use — from AI coding agents to project management and communication platforms. #### Integrating with AI coding agents (Claude Code, Cursor, etc.) via MCP Connect AI Architect to your AI coding agents using the one-command installer, which automatically configures Claude Code, Cursor, Windsurf, GitHub Copilot, and other compatible tools on your system. [**Quick MCP integration guide →**](/ai-architect/quick-mcp-integration-with-ai-coding-agents.md) *** #### Integrating with Jira AI Architect integrates directly with your Jira workspace to bring codebase intelligence into the planning phase. When an Epic or Story is created, AI Architect automatically analyzes your codebase and past tickets to generate a structured plan — covering feasibility assessment, technical design, and story breakdown — directly inside Jira. [**Jira integration guide →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-jira.md) *** #### Integrating with Linear Connect AI Architect with Linear to bring codebase-aware planning into your Linear workspace. AI Architect can analyze your codebase in the context of Linear issues to help teams move faster from planning to implementation. [**Linear integration guide →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-linear.md) *** #### Integrating with Slack Bring AI Architect's codebase intelligence directly into your Slack workspace. Ask questions, get technical context, and collaborate on planning. [**Slack integration guide →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-slack.md) *** #### Integrating with Confluence AI Architect can also connect to your Confluence workspace, treating your documentation as a first-class context source alongside your code and tickets. When a Jira ticket has linked Confluence pages — RFCs, design docs, runbooks, acceptance criteria — AI Architect reads them automatically and grounds its implementation plan in what's already documented. You can also reference Confluence pages from Slack and ask AI Architect to create, update, or comment on pages from inside Jira or Slack. This keeps planning, discussion, and documentation in sync — no tab-switching to copy context around. [**Confluence integration guide →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-confluence.md) *** #### Integrating with chat agents AI Architect works with popular chat-based AI tools so you can query your codebase knowledge graph conversationally. * [**Guide for Claude.ai (Web) →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-chat-agents/guide-for-claude.ai-web.md) * [**Guide for Claude Desktop →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-chat-agents/guide-for-claude-desktop.md) * [**Guide for ChatGPT (Web & Desktop) →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-chat-agents/guide-for-chatgpt-web-and-desktop.md) *** #### Integrating with Bito's AI Code Review Agent AI Architect can work alongside Bito's AI Code Review Agent to provide richer, codebase-aware feedback on pull requests — combining live code review with deep knowledge of your system's architecture and history. [**AI Code Review Agent integration guide →**](/ai-architect/integrating-ai-architect-with-your-tools/integrating-with-bitos-ai-code-review-agent.md) {% endstep %} {% endstepper %} ### AI Code Reviews in Git {% stepper %} {% step %} ### Sign up for Bito Create your account at [alpha.bito.ai](https://alpha.bito.ai/home/welcome) to get started. {% endstep %} {% step %} ### Connect your Git provider Select your preferred Git platform and follow the guided setup to install the agent: * [GitHub](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-github.md) * [GitHub (Self-Managed)](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-github-self-managed.md) * [GitLab](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-gitlab.md) * [GitLab (Self-Managed)](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-gitlab-self-managed.md) * [Bitbucket](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-bitbucket.md) * [Bitbucket (Self-Managed)](/ai-code-reviews-in-git/install-run-using-bito-cloud/guide-for-bitbucket-self-managed.md) Once installed, the agent will be linked to your repositories and ready to assist. {% endstep %} {% step %} ### Review pull requests The AI agent will automatically review **new pull requests** and leave inline comments with suggestions.\ You can also **manually trigger a review** by commenting `/review` on any pull request. [See full list of available commands](/ai-code-reviews-in-git/available-commands.md) {% endstep %} {% step %} ### Chat with the agent You can reply to comments posted by the Bito AI agent in a pull request to ask follow-up questions or request clarification. The agent will respond with context-aware answers to help you understand the feedback better. [Learn more](/ai-code-reviews-in-git/chat-with-ai-code-review-agent.md) {% endstep %} {% step %} ### Configure agent settings To customize your agent, go to [Repositories](https://alpha.bito.ai/home/ai-agents/code-review-agent) and click the **Settings** button next to the relevant agent. From there, you can choose the review feedback mode, enable or disable automatic reviews, define custom guidelines to align with your team’s standards, and more. [Learn more](/ai-code-reviews-in-git/install-run-using-bito-cloud/create-or-customize-an-agent-instance.md) {% endstep %} {% endstepper %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.bito.ai/quickstart.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.