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Open Source AI Agent Platform

An open-source AI agent builder vs a platform a team owns

A builder draws one task as nodes on a canvas. A platform runs a team of agents whose skills, memory, and connectors live as files in one repo. The two give a team different things; Kortix, the open-source AI Operating System, is the platform case.

A builder and a platform, side by side

Kortix first. Each rival column states what that tool's own repository documents.

Recommended

  1. 01

    Open source

    Yes. Read it, fork it, audit it.
    • DifyYes. The community edition self-hosts.
    • n8nFair-code. Source available.
    • LangflowYes. Open source and self-hostable.
  2. 02

    What it is

    The open-source AI Operating System you own.
    • DifyA platform to build LLM apps and workflows.
    • n8nWorkflow automation with native AI capabilities.
    • LangflowA platform to build and deploy agents and workflows.
  3. 03

    How you build

    Markdown agents and files in git.
    • DifyDrag nodes on a visual canvas.
    • n8nA visual canvas, plus custom code.
    • LangflowA visual canvas, plus Python components.
  4. 04

    Agents

    Agents are markdown files in your repo.
    • DifyDescribe the agent and it builds itself.
    • n8nBuild multi-step agents on the canvas.
    • LangflowMulti-agent orchestration with retrieval.
  5. 05

    Where your configuration lives

    Files in one git repo you own.
    • DifyIn the Dify workspace.
    • n8nIn the n8n instance.
    • LangflowIn the Langflow app.
  6. 06

    Self-host

    Self-host is free; cloud, VPC, or on-prem.
    • DifyDocker Compose on your machine.
    • n8nDocker, self-host or cloud.
    • LangflowA Python package or Docker.
  7. 07

    Models

    Any model provider with your own keys.
    • DifyHundreds of LLMs, many providers.
    • n8nOpenAI, Anthropic, Google, open-source.
    • LangflowAll major LLMs.
  8. 08

    Reach your tools

    3,000+ apps, MCP, and any API.
    • DifyMarketplace tools, MCP servers, your APIs.
    • n8n1,500+ integrations and workflow templates.
    • LangflowBuilt-in API and MCP servers.

What a builder gives you

A visual builder is a canvas of nodes. You drag steps, wire them together, and run one flow per task. Dify builds LLM apps and workflows on a visual canvas (Dify); n8n combines a visual canvas with custom code (n8n); Langflow pairs a visual builder with Python components (Langflow). All three keep the configuration in the app's own workspace or instance, which is the shape of a builder. One pure canvas, Flowise, has been archived; its own repository says so and points to a "Future of Flowise" discussion (Flowise).

What a platform gives a team

A platform runs the agents and keeps the system a team owns. Kortix is the open-source AI Operating System: agents, skills, memory, and connectors are files in a git repo you own, with every session on its own cloud computer. An agent is agents/<name>.md (behavior) plus an agents.<name> block in kortix.yaml (governance). One isolated sandbox per session. Each session has its own isolated machine and branch. Session work reaches main through a change request, and merge is default-deny for agents. Any model provider with your own keys, or the ChatGPT plan you already pay for, or sign in with your OpenCode Console account for OpenCode Zen and Go.

The decision

Pick a builder when the job is one flow you design by hand and want to run the same way every time. Pick a platform when a team runs many agents over time and needs shared memory, per-agent permissions, a review gate, and a configuration it owns. A framework is a third case, covered in an open-source platform vs a framework: CrewAI is a Python framework you build with.

Where a builder stops

The canvas is the ceiling. A builder holds one flow at a time, so it has no place for shared company memory, no per-agent permission surface, and no record of who reviewed what. When many people run many agents, and the configuration has to survive a change of vendor, the builder's own workspace is the thing that does not move with you. A platform keeps the orchestration in the same repo as the agents.

A builder flow and a platform agent, in one file

In a builder you draw the same job as nodes. On Kortix it is one agent with a declared reach:

yaml
kortix_version: 2default_agent: kortix agents:  kortix:    file: agents/kortix.md    connectors: [gmail, linear]    secrets: [GMAIL_TOKEN]    kortix_permissions: [project.gitops.push]

Source: https://kortix.com/docs/project/manifest

Where this fits in the field

The builder-or-platform question is one choice among several. The comparison chart lays the main platforms out dimension by dimension, and the shortlist sorts them by the kind of team they fit. For the head-to-head with a workflow engine, read Kortix vs n8n: an open-source agent platform or a workflow engine.

FAQ

Questions about builders and platforms

5/5
  1. Is a visual AI agent builder the same as a platform?

    No. A builder draws a flow of steps, and a platform runs the agents and keeps the system. On Kortix the agents, skills, memory, and connectors are files in a repo you own, and every session runs on its own cloud computer.

  2. Can a team use a builder and a platform together?

    Yes. Many teams keep a workflow canvas for fixed, scheduled flows and use Kortix for open-ended work. The unit of work decides: a fixed flowchart fits a builder, and a job whose steps you cannot list fits a platform.

  3. When should a team pick a builder over a platform?

    When the work is one flow you design by hand and run the same way every time. If the team needs shared memory, per-agent permissions, and a reviewed path to main, a platform is the fit.

  4. Does Kortix have a visual canvas?

    No. Kortix configures agents as files: an agent is agents/<name>.md (behavior) plus an agents.<name> block in kortix.yaml (governance). You edit them in git.

  5. Is Flowise still maintained?

    No. Flowise has been archived; its own repository says so and points to a "Future of Flowise" discussion.

Run the agents, don't just draw them

One repo holds the agents, skills, memory, and connectors a team owns.