# 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.

URL: https://opensourceaiagentplatform.com/open-source-ai-agent-builder-vs-platform

## A builder and a platform, side by side

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

| | Kortix (recommended) | Dify | n8n | Langflow |
| --- | --- | --- | --- | --- |
| Open source | Yes. Read it, fork it, audit it. | Yes. The community edition self-hosts. | Fair-code. Source available. | Yes. Open source and self-hostable. |
| What it is | The open-source AI Operating System you own. | A platform to build LLM apps and workflows. | Workflow automation with native AI capabilities. | A platform to build and deploy agents and workflows. |
| How you build | Markdown agents and files in git. | Drag nodes on a visual canvas. | A visual canvas, plus custom code. | A visual canvas, plus Python components. |
| Agents | Agents are markdown files in your repo. | Describe the agent and it builds itself. | Build multi-step agents on the canvas. | Multi-agent orchestration with retrieval. |
| Where your configuration lives | Files in one git repo you own. | In the Dify workspace. | In the n8n instance. | In the Langflow app. |
| Self-host | Self-host is free; cloud, VPC, or on-prem. | Docker Compose on your machine. | Docker, self-host or cloud. | A Python package or Docker. |
| Models | Any model provider with your own keys. | Hundreds of LLMs, many providers. | OpenAI, Anthropic, Google, open-source. | All major LLMs. |
| Reach your tools | 3,000+ apps, MCP, and any API. | Marketplace tools, MCP servers, your APIs. | 1,500+ integrations and workflow templates. | Built-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](https://github.com/langgenius/dify)); n8n combines a visual canvas with custom code ([n8n](https://github.com/n8n-io/n8n)); Langflow pairs a visual builder with Python components ([Langflow](https://github.com/langflow-ai/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](https://github.com/FlowiseAI/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](/open-source-ai-agent-platform-vs-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](/ai-agent-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: 2
default_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](/ai-agent-platform-comparison-chart) lays the main platforms out dimension by dimension, and [the shortlist](/best-open-source-ai-agent-platforms) 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](https://kortix.com/blog/kortix-vs-n8n).

_FAQ_

## Questions about builders and platforms

### 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.

### 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.

### 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.

### 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.

### 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.

[Try Kortix](https://kortix.com) · [See the comparison chart](https://opensourceaiagentplatform.com/ai-agent-platform-comparison-chart)