
Content fuels every stage of a business, from promotion to internal workflows, but managing it across platforms can be overwhelming. Today, with media being generated faster than ever across formats like video, audio, blogs, and social platforms, businesses need more than just storage and organization. They need intelligent content discovery. In this episode of the Analytics Insight Podcast, host Priya Dialani speaks with PhaniMohan Kalagara, Chief Technology Officer at Gracenote, to decode the evolving role of media intelligence in the digital era.
Priya opens the discussion with a common challenge that many businesses confront: content overload. The problem here lies in origination; there is far too much content, and the real difficulty lies in filtering relevant content and making it actionable. Agreeing with her, PhaniMohan points out that faster, smarter, and more personalized discovery shall become a must with the exponential rise of content.
He presents AI-powered retrieval augmented generation (RAG) and metadata-driven personalization, describing how these processes offer users meaningful content while aligning suggestions to user interest. This is how the discovery becomes a contextual experience instead of a search process.
Gracenote is spearheading this paradigm shift. Metadata and discovery systems of Gracenote likely work behind the scenes for users searching and streaming content via Google, Amazon, Roku, or LG smart TVs. "In North America, our penetration is close to 90%," Kalagara remarks, "and now we are rapidly growing across Europe and Asia as well."
Mr. Kalagara outlines the key pillars that modern media intelligence platforms must deliver on:
Contextual Relevance: The context is all that matters, be it advertising, commerce, or content streaming. Engagement gets maximized by placing the exact right content or product in front of the user at the right time. On the other hand, an advertiser might find a greater ROI by targeting viewers due to mood, interests at the moment, or their behavior-interest all enabled by contextual AI.
Personalization at Scale: Discovery has to be tailored to one’s preference. PhaniMohan describes how Gracenote enables deeper personalization to solve the problem of having users pinpoint exactly what they want in fragmented digital landscapes.
Commerce Integration: Imagine seeing a dress in a show and buying it instantly—that is the future for contextual commerce. Kalagara believes that media intelligence can close the gap between content and consumer action by recognizing desire in context.
Real-Time Content Tracking: As users will be talking about brands online on tens of thousands of different platforms, the media intelligence tools have to collect, process, and contextualize this information in real time. This is not just about listening; it is about understanding.
GraceNote also supports production studios through tools like Studio Systems, which allow agents and studios to match cast and crew more efficiently, helping build high-performing teams for creative projects.
With its deep penetration in North America and growing footprint in Asia and Europe, Gracenote has become the invisible backbone behind global content discovery. Kalagara, with his rich background in graphics, VR simulations, and now media intelligence, is focused on taking GraceNote further into AI-driven content experiences.
He emphasizes that AI is enabling smarter discovery, not just for consumers but also for businesses — allowing real-time insights, smarter decision-making, and contextual engagement.
Content discovery is no longer just about finding information. It’s about understanding user context, acting in real time, and delivering personalized, actionable experiences across platforms. As PhaniMohan Kalagara sums it up, the fusion of AI, metadata, and contextual intelligence is what powers meaningful discovery in an age of digital overload — and Gracenote is leading that charge.