Shapor Naghibzadeh, a former Google sysops engineer, has co-founded QueryStory, a startup aiming to use large language models (LLMs) to tell data-driven stories. By automatically generating detailed dashboards and analyses, the platform promises to bridge the trust gap between AI-generated insights and human decision-makers.

“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,” explains Naghibzadeh. “It’s about telling stories with data.”

In practice, QueryStory enables users to query large databases and receive sophisticated visualizations in just a few hours, compared to the weeks it might take using traditional methods. The platform also provides a confidence indicator that shows why AI agents believe their analyses are accurate.

“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,” says Tayler Sipperly, a partner at Brightmind Partners. QueryStory’s model-agnostic approach ensures that users benefit from the latest AI advancements without being locked into any specific provider.

The startup has raised $6 million in seed funding and is targeting large enterprises with proprietary databases. Its aim is to provide transparency, reliability, and control as businesses integrate AI into their workflows.