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ElevenLabs Develops Efficient Voice Agent for Document Support
ElevenLabs has made a significant breakthrough in the realm of customer support by developing a voice agent capable of efficiently handling user inquiries related to its documentation. This innovative solution is poised to revolutionize the way companies approach document-based customer support, offering unparalleled efficiency and cost-effectiveness.
The newly developed voice agent is powered by a large language model (LLM) that has been meticulously trained to provide accurate and relevant responses to users’ queries. This technology allows the AI-driven solution to effectively address user inquiries, achieving an impressive resolution rate of over 80%.
According to ElevenLabs, the voice agent processes approximately 200 calls daily, showcasing its remarkable ability to efficiently address a significant volume of inquiries. Furthermore, human validation of 150 conversations revealed an 81% agreement rate between the LLM and human evaluators on successfully resolved inquiries.
Moreover, the AI-powered solution demonstrated an impressive 83% agreement on maintaining adherence to the knowledge base, ensuring seamless and accurate communication with users. Additionally, a staggering 89% of relevant support questions were either answered or correctly redirected by the documentation agent, underscoring its ability to effectively manage straightforward queries.
The voice agent has been specifically designed to excel in resolving specific questions that align well with the available documentation. It efficiently guides users to relevant pages and provides initial guidance on complex queries, proving particularly beneficial for inquiries related to API endpoints, language support, and integration queries.
In order to optimize its performance, ElevenLabs recommends targeting users with clear questions and utilizing redirects for more complex inquiries, further enhancing the efficiency of the support process.
Source: Blockchain.News
