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QueryStory leverages LLMs to synthesize complex database queries into coherent, truth-grounded narratives, addressing the critical need for verified knowledge in enterprise data analysis. By applying cybersecurity-derived techniques to analytics, the startup aims to streamline investigations and reduce the time required to assemble data-driven stories. This approach represents a practical application of AI to enhance data integrity and investigative efficiency within large-scale proprietary systems.
Sursă care acoperăTechCrunch
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QueryStory wants you to believe what AI is telling you

TechCrunch5 min de cititArticolul și perspectiva sunt în engleză.

The startup came out of stealth with $6 million in seed funding and a plan to use LLMs and cybersecurity know-how to make AI queries coherent.

Shapor Naghibzadeh learned the value of a good story in 2009 as a Google sysops engineer. When hackers backed by China set their sights on the search giant as part of an effort dubbed Operation Aurora, he was called into a hastily assembled war room to explain what exactly was going on in the company’s servers. Tracing cyberattacks through disparate networks taught Naghibzadeh the value of verified knowledge. But it was a costly and time-consuming task. He thinks that LLMs can bring that same functionality to databases of all kinds in a fraction of the time. Naghibzadeh…

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