IrisGo

IrisGo identified a friction point that knowledge workers faced daily: repetitive digital tasks consumed hours without adding value. Users spent significant time on routine actions—data entry, file organization, email sorting, screenshot annotation—that followed predictable patterns but lacked automation solutions. This problem hit hardest for professionals managing multiple applications simultaneously, where context-switching between tools multiplied inefficiency. The problem was measurable. Workers could quantify lost hours, and productivity metrics showed clear performance gaps. However, existing alternatives were fragmented: RPA tools required technical expertise and custom coding, while basic automation software handled only narrow use cases. No solution existed that could learn from observation across diverse applications. Early validation came through user testing that revealed immediate recognition of the pain point. When IrisGo demonstrated its ability to watch and replicate user actions, professionals immediately grasped the value proposition. The backing from Andrew Ng—a credible AI authority—signaled that the technical approach was sound, validating that desktop automation through visual learning was achievable rather than speculative.