QueryStory, a data analytics startup co-founded by former Google engineer Shapor Naghibzadeh, emerged from stealth on Wednesday with a platform designed to give enterprises trustworthy answers from their proprietary databases using large language models. The company, which counts Naghibzadeh as CEO, was co-founded with CTO Stanley Yang and CPO David Glusic. It raised a $6 million seed round in late 2025 from Brightmind Partners and New York Life Ventures at a $60 million valuation.
Naghibzadeh’s approach stems from his work at Google, where he traced cyberattacks during the 2009 Operation Aurora incident and later built tools for security analysts to query complex data. He co-founded Chronicle within Google X Labs in 2016 to bring that capability to other firms. With QueryStory, he aims to apply those investigative techniques to general analytics, letting users ask a series of questions and assemble the results into a narrative grounded in verified data.
The product is aimed at large enterprises that manage big, proprietary databases, serving sales teams and operations managers who lack dedicated data science staff. Tim Del Bello, a managing director at New York Life Ventures, said his firm is using the platform to replace several employees’ work on a quarterly business review, with hopes of turning it into a real-time dashboard. He described the tool as built for decision-makers who need to handle complex, disparate data sources in regulated industries without a BI team.
In a demonstration for TechCrunch, QueryStory produced a visualization and dashboards from a database of space activity in a few hours, a task that previously took weeks with a developer. The platform also flagged a confidence indicator explaining why the AI believed its analyses were accurate. This transparency is a key differentiator from co-working tools offered by frontier labs, which Naghibzadeh argues have intentionally limited user experiences.
QueryStory is designed to surface the SQL queries behind its analyses automatically, allowing users to flag results for human review, with those reviews recorded in the platform. Tayler Sipperly, a partner at Brightmind Partners, said AI is more brittle than people realize when relied upon for durable, large-scale business operations. Naghibzadeh warns that connecting a company’s data to a generic chat UI leads to hundreds of people asking questions, getting different versions of the truth, and spreading that content without tying it back to the source data.
The startup is built to be model-agnostic, currently using the latest models from frontier labs, but Naghibzadeh says customers will prefer a provider not incentivized to sell as much compute or token consumption. He argues that a purpose-built tool can be more efficient and accurate than a general-purpose agent by preserving context. The company’s core pitch, he said, is trust in the answers it delivers, giving executives like CFOs a clear understanding of costs.
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