Kortix vs Flowise: an open source alternative to an archived builder

What Flowise was, and why teams adopted it

Flowise is an open source generative AI development platform for building AI agents and LLM workflows, in the words of its own documentation. It put a drag-and-drop canvas in front of that work: three visual builders, named Assistant, Chatflow and Agentflow, covered chat assistants, single-agent systems and multi-agent orchestration. Teams adopted Flowise because they could stand up a chatbot or a retrieval pipeline over their own documents without wiring the orchestration by hand.

Where Flowise stands now

Flowise's repository states, "Flowise has been archived," and a banner on flowiseai.com reads, "We're sunsetting Flowise." The team published the milestones: feature development and pull-request reviews stopped on July 29, 2026, the repository moved to public archive, and end of life arrived on August 31, 2026. The code stays visible and anyone can fork it, but the npm package and Docker images are marked deprecated and nobody is shipping fixes. A team still exposing an archived Flowise instance carries that risk with no maintainer behind it.

What changes when you move to Kortix

Kortix is the open-source AI Operating System. The difference a Flowise team feels first is where the configuration lives. A Flowise setup is assembled on a canvas and stored inside the Flowise app; a Kortix project is a git repo you own, with kortix.yaml at its root and agents, skills, memory and connectors as files inside it. Each session runs one agent in its own sandbox, and session work reaches main through a change request a person approves. Read the docs

What the migration actually involves

Start by inventorying your flows and splitting them in two. A fixed pipeline that runs the same steps every time still suits a workflow builder, so keep that part where it is or move it to a smaller tool. The open-ended jobs are the part Kortix is built for: reproduce each one as an agent, a markdown persona with its own scoped connectors, and move the connectors your old nodes used so the agent reaches the same apps.

Then let the work arrive as something you can read first. An agent proposes its output on its session branch and you review the diff before it merges, so a person stays on the gate instead of trusting an unmaintained runtime. Kortix on GitHub shows where the agents, skills and memory files sit in the repo.