Kortix vs LibreChat: multi-model chat, or an open-source system a team owns

LibreChat is the strong self-hosted chat interface teams use to reach many model providers from one window; Kortix is the open-source AI Operating System a company adopts when work has to leave the chat window. Both point at the models you choose, and both self-host. They part ways when a team needs one shared brain across every agent and every session, and a way to review work before it lands.

What LibreChat is great at

LibreChat is a self-hosted web application that unifies many providers in one chat interface. A team can run the whole thing under the MIT licence.

• One window, many providers. The project unifies Anthropic, AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, any OpenAI-compatible endpoint, and Ollama, so a team stops opening a tab per model (LibreChat on GitHub).
• Sandboxed code in real languages. Its Code Interpreter runs Python, Node.js, Go, C/C++, Java, PHP, Rust, and Fortran in an isolated sandbox, built on the open-source ClickHouse code-interpreter service (Code Interpreter docs).
• Approval controls on code. An admin can set Ask, Allow or Deny for file writes and command execution, so an agent can wait for a person before it writes (LibreChat on GitHub).
• Subagents with their own context. An agent delegates focused work to isolated child runs that carry their own context windows (Subagents docs).
• A real admin panel. A standalone panel manages people, groups, roles, and per-role configuration overrides over OAuth2, LDAP, or email login (Admin panel docs).

Its homepage counts 45.6k GitHub stars and 57.1M Docker pulls, checked October 2026 (LibreChat homepage). LibreChat is MIT licensed, which lets a team run and change it freely (MIT licence).

Where a chat UI stops for a team

LibreChat is built around the conversation, so its state stays close to the chat. That shape fits a person or a chat-first team. It strains once the company itself is what has to remember and review.

• Memory is per user. LibreChat's User Memory is a key/value store that persists information about one person across their conversations, and an agent uses that personal pool by default (memory docs). Nothing there is a store the whole company writes to and every agent reads.
• Files and history stay in the conversation. Uploads, code-interpreter outputs, and message history belong to a conversation or its sandbox workspace, so they do not accumulate into shared knowledge (code interpreter docs).
• The unit of work is the chat. A finished answer is a message in a conversation. There is no branch that records what changed, and no change request a person merges before it counts.
• State lives in the product. Saved agents, conversations, and memory entries sit in LibreChat's own database, and the admin panel manages overrides there too (admin panel docs). You inspect the company by querying that product.

These are limits for a company that needs shared state and a review gate. They are not flaws in what LibreChat is, which is a self-hosted chat and agent surface over the models a team already pays for.

The company is one git repo

Kortix takes the other route. It stores the agents, the skills they share, the company's memory, the connector configuration, and the triggers as files in one git repo you own (Kortix docs).

Because those are files, the company is versioned and diffable. A new teammate clones the repo and gets the agents, the skills, and the memory the agents have built up. One agent's finding is available to the next person and the next session. You can grep the whole company and roll any part of it back.

# kortix.yaml
agents:
  support-triage:
    file: agents/support-triage.md
    connectors: all
triggers:
  - slug: daily-digest
    type: cron
    cron: '0 0 9 * * 1-5'
    prompt: Summarize yesterday's support tickets and open a change request.

Agents are markdown, memory is plain files, and kortix.yaml declares the machine image, the connectors, and the triggers. Nothing about the team's configuration hides inside someone else's database.

Every session lands as a change request

Each Kortix session runs on its own isolated cloud computer, on a branch named after the session. The agent can install packages, run code, and break things, and only what it commits survives (Kortix on GitHub).

Work reaches the default branch through a change request a person reads as a diff, so nothing lands unreviewed. You set each connector call to allow, ask or block, and you choose the model per agent with your own keys. Run it on Kortix Cloud, in your VPC or on-prem, or self-host for free.

Where LibreChat is the better pick

For a team whose work really is conversation, LibreChat is the simpler choice. It runs from one Docker Compose stack (MongoDB, MeiliSearch, and a RAG API) or a one-click Railway deploy, and its MIT licence means nothing to buy (Quick Start docs).

If you want a self-hosted, model-agnostic chat surface with per-user memory and sandboxed code, and you do not need one shared company brain or a review step before work lands, LibreChat gets you there with less setup than Kortix.

Side by side

When to pick which

If you are still mapping the field, the open-source AI agent platform guide weighs the whole category, the self-hosted AI workspace roundup compares six options for a team, and the Open WebUI comparison covers the chat-first route beside this one.

Give your agents one system the whole team owns. Free to start, free to self-host. Get started with Kortix.