A New AI Startup Wants to Read Your Company's Data and Tell You What It Means
A startup called QueryStory launched publicly on August 26, 2026, with $6 million in funding and a $60 million valuation. Brightmind Ventures and New York Life Ventures led the investment, according to a TechCrunch report published the same day. The company's website is querystory.ai.
QueryStory says it turns company data into stories that business teams can act on (QueryStory Newsroom). Think of it like hiring a research assistant who can read through all your company's files, databases, sales records, and even recorded phone calls, then write up a summary of what matters.
The platform connects to many types of data. That includes organized information like spreadsheets and customer databases, as well as less organized material like call recordings and presentation slides. It works with three popular cloud data services: Snowflake, Databricks, and BigQuery. Users can get the results as a slide deck, document, dashboard, or message.
The company sells its platform to teams in finance, marketing, sales, operations, and data analysis. QueryStory says customer data stays in the customer's own cloud storage, under their own control, and that the company never uses customer data to train its AI.
The founders bring serious experience. CEO Shapor Naghibzadeh helped start Chronicle, a company that came out of Google's experimental X Labs, in 2016. Before that, he was a Google engineer who helped respond to Operation Aurora, a major hacking attack on Google in 2009. CTO Stanley Yang, a former Google colleague, was lead engineer at EvolutionIQ. Chief Product Officer David Glusic previously worked at the consulting firm Accenture.
Tim Del Bello, a partner at New York Life Ventures, invested in QueryStory and also uses it for his own quarterly business reviews. An investor who is also a real customer is worth noting, though it is not unusual in early-stage business software.
The way QueryStory handles data deserves attention. By keeping all AI processing inside the customer's own systems and never training on customer data, the company aligns with what large business buyers now expect. For companies that handle sensitive recordings or financial data, or face strict regulations, this approach reduces a kind of vendor risk that has slowed adoption of AI-powered analytics tools.
The broader context here is the gap between seeing your data on a chart and actually knowing what to do about it. QueryStory's pitch is that AI can sit between raw data, wherever it lives, and the reports that business teams need. Think of the difference between a dashboard full of numbers and a written summary that says, "Sales dropped 12% last quarter, mainly because three large deals slipped into next quarter, and here is what changed." Whether AI can produce that kind of summary reliably enough to replace reports written by people is an open question the market will answer as companies actually use the tool.
If the platform works as promised, it could make life easier for both the technical teams who manage data and the business leaders who need answers. The $60 million valuation suggests investors believe plenty of companies want this kind of tool.
