> 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/ai-architect/installation/install-ai-architect-self-hosted/standalone-mode-vs-enterprise-mode.md). # Standalone mode vs Enterprise mode [Bito's AI Architect](/ai-architect/overview.md) can be self-hosted in **two ways** depending on your use case. Pick the one that matches how you plan to use it: ## 1. Standalone mode (for individuals) A lightweight, single-machine install for individual developers who want to evaluate AI Architect or use it for personal development work. It runs entirely in Docker on your local machine (e.g., laptop) and automatically registers itself with your installed coding agents — no shared infrastructure, no DevOps coordination required. 👉 [**Go to Standalone mode setup guide**](/ai-architect/installation/install-ai-architect-self-hosted/standalone-mode-for-individuals.md) ## 2. Enterprise mode (for teams) A full-featured, multi-user deployment of Bito's AI Architect designed for teams who want to share a centralized knowledge graph across the organization. It supports both **Docker Compose** and **Kubernetes**, can be hosted on any on-premise or cloud infrastructure you control, and includes SSO authentication. 👉 [**Go to Enterprise mode setup guide**](/ai-architect/installation/install-ai-architect-self-hosted.md) {% hint style="info" %} **Note:** Both modes are fully self-hosted on your infrastructure — your code and knowledge graph remain entirely under your control in either case. {% endhint %} ## Quick comparison | | **Standalone mode** | **Enterprise mode** | | -------------------------- | ----------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- | | **Best for** | Individual developers | Teams & organizations | | **Deployment target** | Single machine (laptop/desktop) | Shared server (on-prem or cloud) | | **Deployment mode** | Docker Compose | Docker Compose or Kubernetes | | **Operating systems** | macOS 12+, Ubuntu 20.04+ | macOS, Linux (Ubuntu, Debian, RHEL, etc.), Windows via WSL2 | | **Shared knowledge graph** | No — per-machine only | Yes — shared across the team | | **Authentication** | Bearer token (local cert auto-managed) | Bearer Token, Bito Auth, or Enterprise IdP (SAML/OIDC) | | **Recommended hardware** | 8 GB+ RAM, 4+ CPUs, 50 GB+ disk | 8–12 GB RAM, 6–8 cores, SSD | | **IDE auto-registration** | Yes — Claude Code, Cursor, Windsurf, VS Code, Junie, JetBrains AI | Via [quick-setup installer](/ai-architect/quick-mcp-integration-with-ai-coding-agents.md) or manual config | ## Common prerequisites Regardless of which mode you choose, you'll need the following before you start. Each setup guide covers these in full detail: * A **Bito account** and **Bito Access Key** — sign up at [https://alpha.bito.ai](https://alpha.bito.ai/) and generate a key from [**Settings → Advanced settings**](https://alpha.bito.ai/home/advanced). * A **Git Access Token** for your provider — GitHub, GitLab, Bitbucket, or Azure DevOps. * **LLM API keys** — Bito's AI Architect uses Large Language Models (LLMs) to build a knowledge graph of your codebase. Provide an API key for the LLM provider you plan to use, such as: * Anthropic (Claude) * OpenAI (GPT) * Portkey * Google Vertex AI * Azure AI * Novita * AWS Bedrock * Google Gemini * Local OpenAI-compatible (bring your own server) * **Docker Desktop** (or Docker Service on Linux) running on the host machine. ## Not sure which mode to pick? * If you're a single developer trying AI Architect for the first time on your own machine, start with **Standalone mode**. It's the fastest way to get up and running. * If you're rolling out AI Architect to a team, need a single shared knowledge graph across developers, or have requirements like Kubernetes or SSO, go with **Enterprise mode**. {% hint style="info" %} You can always start with **Standalone mode** to evaluate AI Architect on your own machine, and move to **Enterprise mode** later when you're ready to roll it out to your team. {% endhint %} ### Next steps * [**Standalone mode setup guide**](/ai-architect/installation/install-ai-architect-self-hosted/standalone-mode-for-individuals.md) * [**Enterprise mode setup guide**](/ai-architect/installation/install-ai-architect-self-hosted.md) * [**Available CLI commands**](/ai-architect/installation/install-ai-architect-self-hosted/available-commands.md) --- # Agent Instructions This documentation is published with GitBook. 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