> 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. Pick the product you want to set up from the list below, and you'll find everything you need to get started. * [**Governor**](#governor): cut coding agent spend across Claude Code, Cursor, Codex, and other AI coding tools. Governor gives each request code context up front and routes it to the best model for the task. * [**AI Architect**](#ai-architect): connect AI coding agents, Jira, Linear, Slack, Confluence, and chat agents to a living knowledge graph of your code, business context, and tribal knowledge. * [**AI Code Reviews in Git**](#ai-code-reviews-in-git): get automated pull request reviews in GitHub, GitLab, and Bitbucket. ## Governor {% stepper %} {% step %} ### Prerequisites To start with Bito-hosted Governor, request access by contacting us at . Bito sets up your account and sends your Admin Token. {% endstep %} {% step %} ### Choose a deployment Governor runs either on Bito's infrastructure or inside your own network. | Deployment | Best for | Setup guide | | :-----------------------------: | -------------------------------------------------------------------- | --------------------------------------------------------------------------------- | | **Bito-hosted** | The fastest start. Bito manages infrastructure and updates. | [View setup guide](/governor/set-up-bito-governor-bito-hosted.md) | | **Self-hosted with Docker** | Data residency, egress, or regulatory requirements on a single host. | [View setup guide](/governor/set-up-bito-governor-self-hosted-with-docker.md) | | **Self-hosted with Kubernetes** | Teams that run production services on their own cluster with Helm. | [View setup guide](/governor/set-up-bito-governor-self-hosted-with-kubernetes.md) | Before you start, have these ready: * An API key for each LLM provider you plan to use, such as Anthropic, OpenAI, or Google. * The exact model names your coding tools request. Model names are case sensitive. * An AI Architect MCP URL and access token, if you plan to enable AI Architect. You can find both in your Bito account. {% endstep %} {% step %} ### Add LLM providers, set up routing, and gateway keys Sign in to the Governor admin UI with your Admin Token, then configure three things: * **Accounts:** add each LLM provider API key and test the connection. * **Routes:** map each model name your tools request to a provider account and upstream model. Add more than one target on the same alias for failover and load balancing. * **Keys:** create one gateway key per team or tool, so you can revoke each one on its own. Keys start with `gw_sk_` and appear only once, so copy each key when you create it. {% endstep %} {% step %} ### Enable AI Architect and auto-routing In the Governor admin UI, open **Features** tab. Enable the **AI Architect** feature to serve system context inside every request, and set an **Architect model** to a cost-efficient model, since that sub-agent captures most of the cost savings. Then open **Routes** and turn on auto-routing for a model alias. The router sorts each request into a Simple, Medium, Complex, or Reasoning tier and sends it to the model you assign to that tier. New routers start in Shadow mode, which records what the router would have done and estimates savings while live traffic keeps its original route. Leave the router in Shadow for about a day of real traffic, review the results, and then switch the mode to On. Read [Auto AI model routing](/governor/auto-ai-model-routing.md) for more details. {% endstep %} {% step %} ### Point your coding tools at Governor Set your tool's base URL to Governor and its auth token to your gateway key. For Claude Code, set two environment variables and start the tool. ```shellscript export ANTHROPIC_BASE_URL="https://gateway.bito.ai" export ANTHROPIC_AUTH_TOKEN="gw_sk_..." claude ``` The **Documentation** page in the Governor admin UI gives copy-paste setup for Claude Code, Cursor, Cline, Continue, Aider, Codex CLI, GitHub Copilot CLI, Windsurf, Zed, and any OpenAI-compatible or Anthropic-compatible tool. To roll Governor out to a team, distribute the two variables through your existing developer environment tooling. {% endstep %} {% step %} ### Verify your setup Use **Test** in the admin UI to confirm route selection, send a sample request, and check that it appears in **Reports** with its model, tokens, and cost. {% hint style="info" %} For self-hosted deployments, the [Available commands](/governor/available-commands.md) page covers upgrades, backups, and workspace management. {% endhint %} {% endstep %} {% endstepper %} ## 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` 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 what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.