Shapor Naghibzadeh learned the value of a good story in 2009 as a Google sysops engineer. When hackers backed by China set their sights on the search giant as part of an effort dubbed Operation Aurora, he was called into a hastily assembled war room to explain what exactly was going on in the company’s servers. Tracing cyberattacks through disparate networks taught Naghibzadeh the value of verified knowledge.
But it was a costly and time-consuming task. He thinks that LLMs can bring that same functionality to databases of all kinds in a fraction of the time. Naghibzadeh would spend the next six years focused on the nexus of data and cybersecurity, using Google’s resources to build tools that allowed security analysts to query complex data.
In 2016, he co-founded a startup in Google’s X Labs called Chronicle that would bring that same functionality to other companies. Last year, as large language models took a larger role in data analysis, Naghibzadeh saw a new opportunity to take the techniques he developed for cybersecurity and apply them to a variety of analytics. He co-founded QueryStory, where he is CEO, alongside CTO Stanley Yang, a former Google colleague and lead engineer at EvolutionIQ, and CPO David Glusic, an Accenture veteran.
The startup emerged from stealth today. It’s about telling stories with data, right? Putting a narrative together that’s grounded in truth.” QueryStory raised a $6 million seed round in late 2025 from Brightmind Ventures and New York Life Ventures at a valuation of $60 million, and has spent the intervening time developing and piloting its product with customers.
QueryStory is aimed squarely at large enterprises that manage big, proprietary databases; it serves as a platform to unite data analysis and review for users like sales teams or operations managers. He is also using the platform to replace the work of several people and produce a quarterly business review, which he now hopes will become a real-time dashboard. I shared a database of space activity that’s useful for understanding what companies like SpaceX are doing on orbit.
QueryStory produced a visualization of that data in a few hours, a project I once did with a developer that took several weeks. It produced sophisticated dashboards and analysis, and perhaps most notably, broke out a confidence indicator that showed why the AI agents believed the analyses were accurate. This kind of work can be done with co-working tools built by the frontier labs, but those tools are intentionally limited in their user experiences.
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