OPEN TALK (API): Conversation Intelligence: Enabling Conversation Driven AI Is as Easy as Hitting a Few Endpoints

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OPEN Stage A
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Toshish Jawale
Symbl.ai, CTO & Co-Founder

Toshish Jawale is co-founder and CTO of Symbl.ai. He drives and executes Symbl.ai’s cutting-edge technology roadmap overlaid with business value for developers and enterprises built on a foundation of contextual conversation intelligence. Prior to Symbl.ai, he spent over a decade building from the ground up enterprise-grade intelligence systems. With deep industry expertise in NLP and AI Systems, Toshish focuses on building conversation intelligence technology for Human-to-Human Conversations to enable developers build applications powered by cutting-edge conversation intelligence with ease.


Conversation Intelligence (CI) enables developers to take their applications beyond basic speech recognition, and build more intelligent speech and conversation-driven functionalities and product experiences. Applications, enabled by CI, are not only able to understand the spoken words, but are capable of comprehending the context of entire conversations.

CI is a rapidly growing sector of AI, and has given rise to a new generation of AI-driven products such as Gong, Outreach, RingDNA, and more. Applications, driven by CI, are able to monitor, extract, and analyze contextual insights and conversation intelligence in real-time to automate workflows, increase revenue, elevate productivity, and provide more pleasant and innovative customer experiences.

Building and extending applications with CI-enabled functionalities and experiences no longer require developers to have any working knowledge of building or training their own machine learning models. Hitting a few end points is all it takes to enable CI-driven experiences. Some of the real life examples of how CI is being leveraged in everyday applications are products for sales and revenue intelligence, Agent Coaching, webinar platforms, accessibility, compliance, recruitment and more.

In this session, we will cover the key characteristics of the conversation intelligence API that enable developers to easily build and go-live with intelligence. We will talk about various AI aspects of conversation intelligence such as speech-to-text, extracting various contextual insights, summarizing conversations, generating domain-specific insights and intelligence, topics modeling for conversations and accessing advanced conversation analytics. We will discuss the difference between domain-specific and domain-agnostic CI. We will also take a look at an example to showcase the combination of few of these with the actual code.