The Origin Story
There was still this missing piece. People just weren't really experiencing magic moments of AI in their day-to-day lives.
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From Breakthrough to Application
The story of Worktrace begins with a shared frustration, one observed from two very different vantage points. Angela Jiang, who spent years at OpenAI helping bring ChatGPT-3.5 and GPT-4 to market, watched as the world celebrated AI breakthroughs while enterprises struggled to find meaningful applications. Deepak Vasisht, a computer science professor at UIUC and former Microsoft Research scientist, saw the same disconnect from the research side: powerful AI models sitting idle because organizations couldn't figure out where to deploy them.
The Idea Takes Shape
Their paths crossed at South Park Commons, a San Francisco community for founders and technologists exploring their next ventures. Angela had spent over a year after OpenAI meeting with enterprise leaders and policymakers, consistently encountering the same roadblock: companies were eager to adopt AI but couldn't identify the right use cases. Deepak had been wrestling with a parallel question - how to bridge the gap between breakthrough research and real-world impact.
"It often took months just to find a meaningful use case," Angela recalls. The problem wasn't the technology, it was the translation layer between what AI could do and what people actually needed it to do in their daily work. Together, they realized the answer was hiding in plain sight: use AI to understand work itself.
This insight became the foundation of Worktrace, a platform that observes how people actually work across their tools and systems, then identifies where AI can create the most value. It's a meta-approach: using AI to accelerate the adoption of AI.
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