For the complete documentation index, see llms.txt. This page is also available as Markdown.

Standalone mode vs Enterprise mode

Deploy AI Architect in your own infrastructure for complete data control and enhanced security

Bito's AI Architect 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 β€” no shared infrastructure, no DevOps coordination required.

πŸ‘‰ Go to Standalone mode setup guide

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.

πŸ‘‰ Go to Enterprise mode setup guide

Note: Both modes are fully self-hosted on your infrastructure β€” your code and knowledge graph remain entirely under your control in either case.

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 β€” per-machine only

Yes β€” 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 β€” Claude Code, Cursor, Windsurf, VS Code, Junie, JetBrains AI

Via quick-setup installer 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 β€” sign up at https://alpha.bito.ai and generate a key from Settings β†’ Advanced settings.

  • A Git Access Token for your provider β€” GitHub, GitLab, Bitbucket, or Azure DevOps.

  • LLM API keys β€” 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

  • 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.

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.

Next steps

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