Abstract

Organizations can face significant challenges in assessing operational health due to siloed data sources and the absence of standardized metrics. Critical data, scattered across various departments with disparate databases, can hinder a comprehensive view of performance and cause delayed decision-making and inefficient resource allocation. This disclosure describes techniques that leverage generative artificial intelligence to ingest data from diverse data sources, generate key operational metrics, and provide operational insights via a user-friendly conversational interface. The techniques result in automated, data-driven decision-making; improved operational efficiency; data democratization; support for simplified data exploration; and powerful insight generation.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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