Yellow.ai Launches Generative AI-Powered Email Automation

Yellow.ai, a provider of generative artificial intelligence-powered customer service automation, today launched Email Automation, which it says is capable of handling up to 80 percent of incoming email queries.

Powered by large language models (LLM), the solution can comprehend complex, unstructured emails and infer the object and urgency of the email. It identifies the user and delivers a contextual response grounded in user insights. Yellow.ai says it can reduce ticket volume by up to 80 percent, improve first-contact resolution by up to 20 percent, and cut operational costs by up to 60 percent.

Yellow.ai Email Automation empowers customer support teams with the following:

• Automated Workflow Triggering: Leveraging natural langauge processing, the solution triggers workflows based on email intent, from fetching answers from knowledge bases to escalations and agent transfers.
• Agent Assist: When the email is directed to human agents, they receive generative-AI powered response assistance.
• Simplified Classification of incoming emails based on intent, urgency, customer segment.
• Integrations with leading ticketing and CRM systems.

"Our customers have emphasized the critical need for a solution addressing the challenges of managing email queries efficiently and promptly. Industry surveys reveal that 62 percent of companies do not respond to customer service emails, and when they do, the average response time is around 12 hours, which is highly detrimental to the customer experience," said Raghu Ravinutala, CEO and co-founder of Yellow.ai, in a statement. "With Email Automation, we're revolutionizing how businesses manage customer email inquiries. What sets it apart is that, powered by our YellowG LLM, it ensures a hallucination rate of less than one percent, guaranteeing accurate and contextually appropriate human-like responses. The launch also aligns with our broader mission to redefine the future of customer service with solutions that effectively address the nuanced challenges faced by enterprises."