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 — no shared infrastructure, no DevOps coordination required.
👉 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.
👉 Go to Enterprise mode setup guide
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 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 and generate a key from Settings → Advanced settings.
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.
Next steps
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