Best Self-Hosted AI Workspaces for Teams: A Practical Comparison

Choosing a self-hosted AI workspace for your team means evaluating more than just model support. You need shared company memory, permission scoping, isolated execution, and human review gates — criteria most home-lab tool lists and vendor blogs never address.

After reviewing the documentation and licenses of six self-hosted platforms, here is how they compare on team-oriented criteria.

TL;DR: Which platform for which team?

Platform	License	Best for
Open WebUI	Custom (branding-required, source-available)	Teams wanting a rich chat UI with RBAC, multiple Ollama/OpenAI models, and local RAG — but no company-wide shared memory
AnythingLLM	MIT (OSI open source)	Document-first RAG workflows under a permissive license; Docker required for multi-user
LibreChat	MIT (OSI open source)	Multi-model chat with strong model switching, sandboxed code interpreter, and per-role code approval controls
Dify	Modified Apache 2.0 (source-available)	Visual AI app and workflow builders with low-code tooling and enterprise SSO
n8n	Sustainable Use License (fair-code, source-available)	Workflow automation with AI nodes and human-in-the-loop approval steps
Kortix	Elastic License 2.0 (source-available, not OSI open source)	Teams needing an integrated self-hosted AI Management System with shared git-backed memory, per-session isolated execution, and configurable approval gates for agents

What distinguishes a team-ready workspace

A self-hosted AI workspace for a team needs six capabilities that personal AI tools lack:

• Shared company knowledge — memory that persists across sessions and is available to every authorized user and agent, not per-user chat history
• Multi-agent orchestration — multiple agents coordinating, not a single assistant
• Permission scoping — role-based access per resource, with LDAP/SAML/OAuth integration
• Isolated execution — every agent session runs in a disposable sandbox (container or microVM), not in the server process
• Human-in-the-loop gates — configurable approval before agents write files, send messages, or modify records
• Model choice and data ownership — bring-your-own-API-key, prompts never leave your infrastructure

Where Kortix fits

Kortix is designed as a self-hosted AI Management System, not a chat interface or a framework. Its configuration lives in a git repository the team owns — shared skills, memory (under memory/), and connectors are versioned, diffable, and reviewable. Agents run in per-session disposable Linux sandboxes (containers by default, microVMs with a compatible provider). Human review is built in: change requests for repository work, configurable approval gates, and merge-deny-by-default for agents keep the team in control.

Kortix uses an Elastic License 2.0 (source-available, not OSI-approved open source) — the repository is inspectable and self-hostable via Docker Compose, but the license restricts providing a hosted service that exposes a substantial set of its features. Repository · License · Self-hosting guide

How to choose

Start with your team's primary need. If you need a rich chat UI with RBAC, evaluate Open WebUI or LibreChat. If document RAG is the core use case, AnythingLLM is the strongest candidate. For visual workflow builders, Dify fits. For workflow automation with AI, n8n is purpose-built. And if you want an integrated system where shared memory, multi-agent orchestration, permission scoping, isolated execution, and review gates are designed as one product, Kortix is the documented fit.

All evidence was reviewed from primary repositories and official documentation on September 20, 2026 — this is a documentation-based comparison, not a hands-on benchmark or security certification.

Originally published on the Kortix Blog.