Authenticx Launches Ava, an AI-Powered Assistant

Authenticx, a conversation intelligence platform for healthcare organizations, today launched Ava, an AI-powered in-app assistant that helps users answer business questions while serving up meaningful insights from their own data. The AI assistant can analyze call transcripts, interpret correlations between AI models, provide coaching feedback on agent performance, and recommend strategic actions to take based on learnings from this analysis.

Behind a chat-based interface, Ava uses a large language model (LLM) to interpret user questions and complete analysis of tasks or actions. Responses and recommendations are generated from proprietary Authenticx AI models and users' data. Ava provides context and pattern recognition.

"Customer conversations can help healthcare organizations learn more about their experiences, operational challenges, and more. Our AI strategy has always been to make these insights more accessible," said Eric Prugh, chief product officer of Authenticx, in a statement. "Rather than navigating the breadth of Authenticx's platform, healthcare leaders can now use Ava to chat directly with their organization's data and access insights that were impossible or too time-consuming to access before."

Ava can do the following:

• Provide users with tailored insights, recommended next-best actions, and emerging trends specific to their organizations.
• Synthesize complex findings to prioritize high-impact initiatives, analyze report results, and summarize overarching themes across conversations.
• Generate agent coaching notes, analyze customer conversations, and find relevant audio clips for employee training.
• Onboard new analysts and team members.

"Our recent annual report showed that organizations using conversational AI were able to reduce customer friction by 28 percent on average," said Amy Brown, founder and CEO of Authenticx, in a statement. "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."