This AI Conversational Startup is Helping Sales Professionals Monitor Client’s Mood During Sales Calls

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During the COVID-19 pandemic, almost everything is transitioned to an online mode. Everything is done via video calls from sales calls to online lectures, whether for business or education. However, it differs significantly from face-to-face interactions. You can’t comprehend the other person’s tone or feelings during an internet call. This is a significant concern for sales professionals because developing connections is a critical component of the work. Virtual sales meetings have made it more difficult for sales professionals to read the room than ever before.

Uniphore, a Conversational Automation startup, is developing AI-powered tool to help humans understand and respond to human emotions. During a video conversation, the software attempts to determine whether a potential customer is interested in what a sales professional has to say, notifying the sales professional in real-time if someone appears more or less engaged in a specific issue.

With technology that allows automated, human-like interactions, it can personalize every communication. Uniphore Conversational AI understands sentiment and purpose and can comprehend many languages.

Uniphore’s product, Q for Sales, combines computer vision, speech recognition, natural-language processing, and emotion AI to detect behavioral cues such as a person’s tone of voice, eye and facial movements, and other nonverbal body language and analyzes the data to determine their emotional attitude. It may reveal the customer’s feelings and emotions at any stage throughout the sales interaction. It increases EQ and gives sales teams the contextual information they need to succeed.

The California-based startup has made a new addition to its Conversational AI platform. They have introducedย U-Assist In-Call, which uses Robotic Process Automation(RPA) to assist the users in analyzing the customers’ tone, intent, and sentiments. It will automate call summaries and classification, reducing agents’ time on manual after-call work (ACW). With real-time voice transcription and AI that predicts emotion and intent, it will provide in-call notifications and customize every customer’s experience.ย 



Consultant Intern: Currently in her third year of B.Tech from Indian Institute of Technology(IIT), Goa. She is an ML enthusiast and has a keen interest in Data Science. She is a very good learner and tries to be well versed with the latest developments in Artificial Intelligence.

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