QueryStory has emerged from stealth with a platform designed to make AI-generated business analysis easier to inspect. The startup raised a $6 million seed round from Brightmind Ventures and New York Life Ventures at a reported $60 million valuation.
Users can ask questions across large proprietary databases and receive dashboards and narrative explanations. Unlike a basic chat interface, the product surfaces the SQL queries behind an analysis, provides confidence indicators and lets colleagues flag results for human review. Those reviews remain attached to the work, creating a record of how a conclusion was checked.
The company is targeting sales, operations and other enterprise teams that need answers but may not have direct access to data scientists. Its founders draw on cybersecurity work, where investigators must connect events across several systems and preserve evidence for each claim.
QueryStory is model-agnostic, though it currently relies mainly on models from major AI labs. The extra audit layer cannot guarantee that an analysis is correct: confidence measures, generated SQL and source data can all be flawed. Its practical value will depend on whether the visible trail helps people catch those errors before a chart or narrative drives a business decision.