MuleRun runs AI agents on dedicated persistent computers rather than inside a chat session. An agent opens tools, follows multi-step workflows and returns finished results, working around the clock without anyone prompting it. The company describes the workforce as self-evolving, learning from workflow patterns across the platform, and proactive – watching metrics and acting before an alert fires.
Persistence is the difference that matters and it is an architectural one. A chat-based agent exists only while someone is talking to it, which rules out every task whose value is in noticing something at three in the morning. Giving each agent its own machine that stays running converts the model from a tool you operate into something closer to a service that runs.
Demonstrated work includes branded PowerPoint decks, stock analysis with charts, animated video, news research and formatted documents. There is a free account for initial workflows and no pricing figures on the homepage. An always-on agent accumulates cost whether or not it accomplishes anything, learning from patterns across other customers’ workflows is worth understanding before sensitive work goes near it, and proactive action without a prompt is exactly the capability that needs the tightest limits.
