QueryStory wants you to believe what AI is telling you
Get the Tech newsletter
Daily tech — startups, AI labs, chips, the launches that shape the next decade. Free.
- QueryStory emerged from stealth with a $6 million seed round raised in late 2025 from Brightmind Ventures and New York Life Ventures at a $60 million valuation, targeting large enterprises with proprietary databases.
- Shapor Naghibzadeh, QueryStory's CEO and co-founder, was a Google sysops engineer during the 2009 Operation Aurora response and later co-founded Chronicle inside Google X Labs in 2016 to extend query-based investigation tools to enterprise security.
- QueryStory's platform surfaces the underlying SQL queries automatically and lets users flag AI-generated analyses for human review, recording those reviews in the platform — transparency the company says co-working tools from frontier labs deliberately limit.
- Tim Del Bello, a partner at investor New York Life Ventures, is using QueryStory himself to produce a quarterly business review he hopes to turn into a real-time dashboard, replacing the work of several people in a regulated industry.
- Tayler Sipperly of Brightmind Partners told TechCrunch that "AI is more brittle than people realize when it comes to like building things that have to be durable and have large scale businesses relying upon them."
- QueryStory is built to be model-agnostic and currently leans on frontier-lab models, with Naghibzadeh positioning the company against providers incentivized to "sell as much intelligence as possible" through token-based consumption.
Why it matters: QueryStory is pitching verification infrastructure at a moment when enterprises are letting hundreds or thousands of employees query company databases with LLMs and producing conflicting 'versions of the truth,' per Naghibzadeh. If the $60M-valuation startup delivers visible SQL, human review flags, and confidence scores, it gives CFOs and operations leads a way to shrink analyst headcount and forward-deployed consulting spend without sacrificing oversight — a $6M bet that trust, not raw model power, is the missing layer in the enterprise AI stack.
Ask SkimNews
