Led by former Google engineer Shapor Naghibzadeh, QueryStory has raised $6 million to bridge the trust gap in AI-driven data analysis for large enterprises.

  • QueryStory secured $6 million in seed funding at a $60 million valuation.
  • The platform aims to provide transparency and 'ground truth' in AI-generated data narratives.
  • It features a unique confidence indicator to explain AI reasoning.

In an era where Large Language Models (LLMs) are increasingly used for critical decision-making, a fundamental question remains: Can we trust the answers they provide? To address this, QueryStory, a startup led by former Google systems engineer Shapor Naghibzadeh, has officially emerged from stealth mode with $6 million in seed funding.

The funding round, led by Brightmind Ventures and New York Life Ventures, values the company at $60 million. QueryStory is designed to transform how large enterprises interact with their proprietary databases, turning fragmented data points into coherent, verifiable narratives grounded in truth.

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Why This Matters

BozokMedia analysis shows that as corporations integrate AI into their workflows, the 'brittleness' of these models—their tendency to hallucinate or provide unverifiable outputs—poses a massive operational risk. QueryStory mitigates this by providing a layer of accountability that general-purpose AI chat interfaces lack.

"The thing that we are selling is the trust in the answers." — Shapor Naghibzadeh, CEO of QueryStory

Naghibzadeh’s vision is deeply rooted in his experience during Google’s 'Operation Aurora' in 2009, where he witnessed the high stakes of verifying data during a massive cyberattack. He realized that while AI can process data at lightning speed, it often lacks the contextual durability required for business-critical tasks. QueryStory solves this by surfacing the underlying SQL queries used by the AI, allowing human experts to audit the logic before acting on it.

One of the platform's standout features is its confidence indicator. Unlike standard AI tools that present answers with absolute certainty, QueryStory provides a breakdown of why the AI believes a specific analysis is accurate. This level of transparency is vital for decision-makers in highly regulated industries who cannot afford to rely on 'black box' algorithms.

The leadership team includes CTO Stanley Yang and CPO David Glusic. Together, they are building a model-agnostic platform, meaning QueryStory can integrate with various frontier models while remaining focused on providing a superior, user-centric experience tailored for sales, operations, and executive teams.

Did You Know?: QueryStory is model-agnostic, meaning it doesn't force users into a specific AI ecosystem, allowing for greater flexibility and cost control.

Frequently Asked Questions

1. How does QueryStory differ from ChatGPT?
While ChatGPT is a general-purpose conversational tool, QueryStory is a specialized enterprise platform designed to provide verifiable, data-grounded narratives with audit trails.

2. Who is the target audience for this platform?
The platform is specifically built for large enterprises, decision-makers, and operations managers who handle complex, proprietary datasets.