AI workflow demos are easy.
Connect a model to a prompt, add a tool, run it once, and the result looks impressive.
Production is where the harder questions begin.
What happens when a document changes in your knowledge base? Can a second machine take over the heavy workflows? Can your team use its existing identity provider? When something fails after three retries, can you see what actually happened?
These are the questions shaping Heym, a source-available and self-hostable platform for building AI workflows on a visual canvas.
