Healthcare conversation intelligence platform Authenticx has launched Ava, an AI-powered in-app assistant that helps users efficiently answer key business questions and generate actionable insights from their data.

The AI assistant can analyse call transcripts, interpret correlations between AI models, and provide coaching feedback on agent performance. For example, Ava can answer questions such as: “What topics are increasing call durations?”, “What’s driving preventable call time?”, and “How can we redirect certain calls to automated systems?”

Further, the assistant provides consultant-level insights around the clock, offering customised recommendations and next best actions based on patterns identified in the user’s data. This feature enables leaders to make informed decisions in no time, ensuring continuous access to relevant information.

Ava also excels in synthesising complex data as it helps users prioritise high-impact initiatives, quickly summarise overarching themes, and analyse results, all within a streamlined process that reduces the burden of data interpretation. Additionally, the assistant automates repetitive tasks such as generating coaching feedback, analysing customer conversations, and identifying relevant audio clips for training, saving valuable time for healthcare teams.

For new team members, Ava facilitates onboarding by helping them quickly understand how to use Authenticx’s AI and interpret customer data. This support reduces the learning curve, allowing analysts and other team members to become effective more quickly.

This release builds on Authenticx’s strategic expansion of its generative AI capabilities. The platform’s GenAI solution enables healthcare organisations to use recorded customer conversations as a key source of business insight.

“Our recent annual report showed that organisations using conversational AI were able to reduce customer friction by 28% on average,” said Amy Brown, Founder & CEO of Authenticx.

“Ava is the latest addition to our well-established AI platform and the next step for healthcare organizations to successfully realize the value of their conversation data.”

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