Shapor Naghibzadeh, a former Google SysOps engineer, co-founded QueryStory after years of working in cybersecurity and data analysis. He noticed that large language models could help streamline data verification processes that were previously slow and costly. Naghibzadeh and his team developed QueryStory to bridge the trust gap between AI and enterprise users by providing reliable, actionable insights from complex databases. The startup aims to serve large enterprises that manage proprietary data, offering a platform that unites data analysis and review for teams like sales and operations. 'What we’re doing is bridging that trust gap for AI to give enterprises answers they can act on,' Naghibzadeh said. 'Instead of renting human judgment and armies of forward-deployed engineers, we productized that.'

QueryStory raised $6 million in seed funding in late 2025 from Brightmind Partners and New York Life Ventures at a $60 million valuation. The company has been developing and piloting its product with customers, focusing on enterprises that need to analyze large, complex datasets. Tim Del Bello, a partner at New York Life Ventures, is 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. '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,' he told TechCrunch.

Naghibzadeh emphasized the importance of transparency and reliability in AI systems, especially for large companies that rely on them for critical operations. He pointed out that connecting data to an LLM’s chat UI can lead to fragmented insights and a lack of centralized information. 'You get hundreds or thousands of people within an organization all asking their questions and getting their version of the truth and putting that in a slide deck and sharing it — you just end up with this huge sprawl of content, and there’s no real place to hang that content that ties back to the data,' he said. QueryStory is designed to be model-agnostic, though it currently uses the latest models from frontier labs. Naghibzadeh believes that customers will prefer working with a service provider that isn’t incentivized to sell as much intelligence as possible.

Source: techcrunch