QueryStory, a startup founded by a former Google security engineer, emerged from stealth today with $6 million in seed funding and a platform designed to help large enterprises trust the answers their AI systems produce from complex data. The company aims to bridge what it calls the “trust gap” in AI-generated analytics, providing a product that combines data querying, narrative generation, and human review in a single interface.
From Operation Aurora to AI analytics
CEO Shapor Naghibzadeh, who previously worked at Google and co-founded Chronicle within X Labs, says the idea for QueryStory grew from his experience tracing cyberattacks like Operation Aurora in 2009. That work required asking a series of questions across disparate data sources and assembling the answers into a coherent narrative—a process he believes large language models can now automate and scale.
“You get this pattern of an investigation—you ask a bunch of questions of the data, and after you have been able to ask a number of questions, you assemble that together into a narrative,” Naghibzadeh told Bitcoin World. “That became the genesis for the name QueryStory. It’s about telling stories with data, right? Putting a narrative together that’s grounded in truth.”
Product and funding
The company raised a $6 million seed round in late 2025 from Brightmind Ventures and New York Life Ventures at a $60 million valuation. It has spent the intervening months developing and piloting the product with customers.
QueryStory is aimed at large enterprises that manage big, proprietary databases. The platform serves as a hub for data analysis and review, targeting users like sales teams and operations managers who need answers without relying on dedicated data science teams.
Tim Del Bello, a partner at New York Life Ventures, is both an investor and a user. He said the platform has replaced the work of several people in producing a quarterly business review, which he hopes will evolve into a real-time dashboard. “The product was built for people like me: decision-makers seeking the ground truth who need to work with complex, disparate data sources but don’t have a data science or BI team at their disposal, especially when operating in a highly regulated industry,” he told Bitcoin World.
Addressing AI’s brittleness
The startup is entering a market where general-purpose AI tools like Claude Cowork are increasingly used for data analysis, but those tools often lack transparency and control. QueryStory aims to differentiate by automatically surfacing the SQL queries its AI agents write, allowing users to flag analyses for human review. That review process is recorded in the platform, creating an audit trail.
Tayler Sipperly, a partner at Brightmind Partners, said the need for such oversight is critical. “AI is more brittle than people realize when it comes to building things that have to be durable and have large scale businesses relying upon them,” he told Bitcoin World.
Why this matters
Naghibzadeh warns that connecting enterprise data directly to an LLM’s chat interface can lead to a “sprawl” of conflicting answers and slide decks, with no central place to tie insights back to the underlying data. QueryStory aims to provide that central place, with a focus on confidence indicators that show why the AI believes its analyses are accurate.
The company is also positioning itself as a model-agnostic alternative to the frontier labs, arguing that customers will prefer a vendor that isn’t incentivized to maximize token consumption. “The thing that we are selling is the trust in the answers, right?” Naghibzadeh said. “Our whole goal is giving the CFO the ability to understand ‘what is this thing going to cost?'”
Conclusion
QueryStory’s emergence highlights a growing concern among enterprises: how to adopt AI without sacrificing reliability and accountability. By combining automated query generation with human review and transparent confidence scoring, the startup aims to make AI-driven data analysis safe for large organizations. Whether it can compete with the resources of the frontier labs remains to be seen, but its early backers and users see a clear need for a purpose-built trust layer.
FAQs
Q1: What is QueryStory?
QueryStory is a platform that helps enterprises analyze complex data using AI, providing a transparent and auditable way to generate insights, with automatic SQL query surfacing and human review capabilities.
Q2: Who founded QueryStory?
QueryStory was co-founded by CEO Shapor Naghibzadeh, a former Google security engineer and co-founder of Chronicle; CTO Stanley Yang, a former Google colleague; and CPO David Glusic, an Accenture veteran.
Q3: How is QueryStory different from using ChatGPT or other AI tools for data analysis?
QueryStory is designed for enterprise-scale data, offering model-agnostic operation, a built-in review workflow, and confidence indicators that explain why the AI produced a particular analysis, addressing the “trust gap” that general-purpose AI tools often leave open.
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