Updated
Updated · TechCrunch · Aug 26
QueryStory Launches Enterprise AI Analytics Platform After $6 Million Seed Round
Updated
Updated · TechCrunch · Aug 26

QueryStory Launches Enterprise AI Analytics Platform After $6 Million Seed Round

2 articles · Updated · TechCrunch · Aug 26

Summary

  • $6 million in seed funding backed QueryStory before it emerged from stealth with an AI platform for large enterprises to analyze proprietary data and route results for human review.
  • The startup says its product tackles a core adoption problem—trust—by surfacing the SQL behind answers, attaching confidence indicators and recording reviewer feedback inside the workflow.
  • CEO Shapor Naghibzadeh, a former Google engineer and Chronicle co-founder, built the company around investigation techniques first used in cybersecurity and later adapted for broader business analytics.
  • QueryStory is targeting customers that want more control than frontier-model chat tools offer, arguing a model-agnostic, purpose-built system can deliver more consistent answers and clearer costs.

Insights

Can QueryStory’s visible SQL and review trail turn enterprise AI from a flashy copilot into a system executives actually trust with decisions?
If enterprise AI’s real bottleneck is trust, not tokens, does QueryStory have a moat incumbents can’t easily copy?
Why did an Operation Aurora veteran build QueryStory to fight AI brittleness with context, oversight, and auditability instead of bigger models?