Kortix vs Activepieces: the open-source AI Operating System or a flow builder

Activepieces is a strong open-source flow builder; Kortix is open source and built for the work a fixed flow cannot capture. Both self-host, and both let a person approve what the software does. The split comes down to the unit of work, because a flow runs the steps you drew and a Kortix session takes a job you can describe but cannot draw.

Compared here:

Activepieces

What Activepieces is

Activepieces is an open-source automation platform that describes itself as "an open source replacement for Zapier" (Activepieces on GitHub). You build a flow by linking a trigger to a set of steps, and the flow runs the same way every time. The project is built on a TypeScript framework it calls pieces, and it publishes all 280+ pieces as MCP servers, so an LLM can call the same connectors an app would. The repository says 60% of the pieces come from the community, and the project notes that its community edition is open source while its enterprise features ship under a separate commercial agreement (Activepieces on GitHub).

Pricing is flat and metered in credits. Free is $0 with 1,000 credits a month, unlimited flows, and up to 5 people. Plus is $20 flat per month for 10,000 credits, then $0.007 per credit past the limit, and it lets you bring your own AI keys. Team is $200 flat per month for 50,000 credits and 25 people, with SSO and standard roles. Ultimate and a separate enterprise tier are custom, and embedding the builder inside your own product starts at $36k a year (Activepieces pricing, checked October 2026). Hosting is cloud or on-premises on every tier.

What Kortix is

Kortix is one system, and the company is its configuration. Your agents, their skills, your company memory, and every connector live as files in one git repo you own (Kortix docs). The unit of work is a session: one isolated sandbox per session, and each session has its own isolated machine and branch. You hand the agent a job in plain language, and it plans its own steps and runs them on that machine. Session work reaches main through a change request, and merge is default-deny for agents, so a person reads the change before it lands.

The parts map to the parts of an operating system. Agents are the programs, connectors are the drivers, triggers are the scheduler, and change requests are the updates. Connector credentials are brokered server-side and never enter the machine, and the connectors reach 3,000+ apps in a click, plus MCP, OpenAPI, Postman, GraphQL and raw HTTP. You choose any model provider with your own keys, per agent, per session or per message.

Where a flow builder fits

• The whole flow stays visible. When the same steps must run in the same order every time, a visual builder shows the path at a glance, and anyone on the team can edit a node.
• The library is already built. Activepieces ships 280+ pieces and publishes each one as an MCP server, so the app you need often already has a piece (Activepieces on GitHub).
• The entry tier is flat. Free is $0 with 1,000 credits a month and unlimited flows, and the paid tiers are flat rather than per-step (Activepieces pricing, checked October 2026).
• Embedding is a product. If you want to put a flow builder inside your own app under your own brand, Activepieces sells exactly that (Activepieces pricing, checked October 2026).

These are the strengths of a flow builder, and Activepieces does that job well. If every job you have is a fixed flow between apps, it covers them with less to learn and a lower starting bill than running Kortix.

Where an agent session fits

• The unit is a session. Hand an agent a job in plain language from the web app, Slack, Teams, email, the CLI or an API, and it decides its own steps on its own machine (Kortix docs).
• One repo is the company. Agents, skills, memory files, connectors and triggers are text you own, so you can grep the whole configuration, diff a change, and roll it back.
• Any model with your keys. Any model provider with your own keys, on the agent, the session or the message you choose.
• A change request on the result. Approval gates you set, off until you set them, and session work reaches main through a change request a person reads.

A trigger can be a cron schedule or a signed webhook, so Kortix runs scheduled work too. The difference is what happens when it fires: an agent does the job and opens a change request, rather than running a fixed sequence of prebuilt steps. Kortix runs on Kortix Cloud, in your VPC, or on your own on-prem network, and self-host is free. Free is $0 with 200 credits per month and 1 project; the team plan is $40 per seat per month with 2,500 credits per month per seat, pooled (Kortix pricing).

Side by side

When to pick which

Pick Activepieces when the job is a fixed flow: the same steps, in the same order, on a schedule or a webhook, with a piece for each app already built. It is the simpler choice for deterministic automation that runs on a clock.

Pick Kortix when the job is open-ended: research, a report, a fix, a campaign, work whose steps you cannot list in advance and whose output a person should approve. Kortix gives that work a real machine, the company's tools and memory, and one repo that holds the whole configuration. Teams that run both kinds of work keep the flow builder for the clockwork and give the rest to Kortix.

Related reading: Kortix vs n8n and how to build reliable AI agent workflows.

Kortix is free to start and free to self-host. Get started with Kortix and hand it the work a flow cannot describe.