Retell AI + AssemblyAI: custom LLM and post-call analytics

Integrating AssemblyAI with Retell AI provides a sophisticated solution for enhancing post-call analytics through two primary methods: utilizing custom Large Language Models (LLMs) via WebSockets and employing AssemblyAI’s post-call speech understanding capabilities. This integration allows Retell AI to leverage AssemblyAI's batch API, which offers advanced features such as speaker labeling, sentiment analysis, and the LeMUR action item extraction, delivering insights that surpass the basic real-time transcription capabilities of Azure and Deepgram. The integration aims to provide detailed analytics post-call, where LeMUR can automatically answer critical questions regarding customer issues, resolution status, follow-up actions, and overall sentiment from the call. Users can customize the analytics to fit various scenarios, such as sales, healthcare, and support, by adjusting the LeMUR prompts. Additionally, AssemblyAI’s full Audio Intelligence suite can be configured to run on every call recording, offering comprehensive features like sentiment analysis and entity detection, thereby enhancing the analytical depth and accuracy of post-call data.

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