Author

Casey Ciniello

Reveal and Slingshot Senior Product Manager @ Infragtistics

Published posts 47

Casey Ciniello is a data and analytics-focused product leader at Infragistics, where she drives strategy and innovation for the Reveal embedded analytics platform and the Slingshot work management solution. With a BA in mathematics and an MBA, she brings an in-depth analytical foundation and business perspective to building products that help organizations turn complex data into actionable insights.

Casey leads the development of analytics-driven capabilities, shaping product direction through deep market analysis, user behavior insights, and evolving business intelligence trends. She works closely with customers to understand how data is used in real-world decision-making and translates those needs into intuitive, high-impact analytics experiences. Casey also serves as the Survey Lead for the annual Reveal Software Development Challenges survey, where she analyzes industry data to uncover key trends in analytics, AI, and modern development practices. Her insights and thought leadership have been featured in Dataversity, RT Insights, SaaSXtra, SD Times, Solutions Review, TechStrong IT, App Developer Magazine, Beta News, Integration Developer News, and UX Planet. She is a frequent webinar presenter on modern embedded analytics, machine learning, data visualizations, and scaling SaaS analytics. Casey joined Infragistics in 2013.

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Conversational Analytics in Embedded Analytics

Conversational Analytics in Embedded Analytics

Conversational analytics gives users a faster way to get insights by letting them ask direct questions instead of building reports. It reduces friction across the product and helps teams deliver clear answers without extra clicks or technical steps. The challenge appears when conversational analytics software relies on external AI services, which creates security and data-control risks. Reveal solves this with an architecture that keeps AI inside your environment and applies your existing rules to every request. You get a secure, flexible layer that supports natural-language queries without exposing your data.

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