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Content Discovery

Significant advances in generative AI in recent years have made artificial intelligence a top priority for businesses globally. As a result, large language models (LLMs) have become foundational in powering everything from virtual service agents to online search engines to fraud detection.

In entertainment media, LLMs will be foundational in powering rich search and discovery experiences, but they can’t do it alone. Because LLMs are prediction engines, they require complementary technologies to fact check the results they provide. These technologies improve accuracy, provide contextual relevance, enrich results, and align LLM outputs with real-world knowledge.

The Model Context Protocol (MCP) is ideal for ensuring that an LLM’s output is a reliable single source of truth facilitating a dynamic connection between an LLM and Gracenote’s knowledge base. This white paper details how MCP facilitates that connection to ensure that search and discovery experiences are rich and personalized, as well as accurate, recent and complete.

Personalized media experiences could drive greater in-car infotainment system use

Drivers want more from their media experiences than what their smartphones offer.

Oct 30, 2025
Drivers are looking for more of what they love from their in-car infotainment systems; data can deliver it

Widespread connectivity notwithstanding, drivers remain enamored with AM/FM radio. On that front, automakers can give them more of what they love.

Oct 22, 2025
2025 Gracenote auto infotainment report

The desire for next-level infotainment among vehicle owners is unmistakable. Comprehensive entertainment data can help automakers deliver on that desire.

Oct 15, 2025









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