Considering a homegrown generative AI solution for conversation intelligence? Here's why it's harder than you think
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Brianna Van Tuinen Brianna Van Tuinen
5 min read
Considering a homegrown generative AI solution for conversation intelligence? Here's why it's harder than you think

Conversation intelligence enables organizations to gain an intimate understanding of their customers' needs, preferences, and pain points, as well as where frontline agents are or are not meeting those expectations. With the emergence of generative AI solutions, the conversation intelligence playing field has been leveled to a certain degree. Every day, the CallMiner team is talking to organizational leaders who are curious if they could harness large language models (LLMs) to build their own in-house conversation intelligence platform.

Building an in-house solution grants organizations some amount of freedom to shape it to their objectives and requirements, and GPT makes the effort seem deceptively easy, but it's ultimately harder than most anticipate. Innovation with LLMs and generative AI is just taking off - and unless you have the right team thinking about this day in and day out, you'll likely be left with a less than desirable in-house conversation intelligence solution, while your competition licenses superior solutions for less.

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