In my last post, Building an AI Travel Agent with Symbl.ai’s Nebula LLM and Amazon Connect, I spoke about how the integration of Generative AI tools are transforming the landscape of call centers, virtual meetings, and many other businesses. I guided you through building an AI Travel Agent leveraging Symbl.ai and AWS that can proactively make personalized recommendations based on a caller’s spoken input and even go as far as to detail flight and accommodation options. All without the need for a human agent.
Now, let’s flip the scenario slightly and turn our AI into a co-pilot, providing Agent Assist to a human agent rather than acting on its own. With instant, AI-enhanced suggestions from the LLM, agents have quick and easy access to a vast amount of up-to-date information to identify, propose, and book our customer the trip of a lifetime (or just to visit me in Punjab!) Symbl’s conversational AI tools can step in after the call with everything from summaries and action items to quality scores.
All of this takes place within Amazon Connect, the AWS cloud-based contact center. A significant advantage of Amazon Connect is its ability to seamlessly integrate with other AWS services and third-party applications, such as we are doing today with Symbl.ai’s Nebula LLM and Streaming API. Please refer back to my previous post to learn more about the powerful features and benefits of these three main players in this project.
I hope these posts are a portal to understanding how these powerful tools can be harnessed to redefine the standards of customer interaction, agent assistance, and post-call analysis. We’re not just talking about incremental changes; we’re delving into a paradigm shift that empowers agents with unparalleled insights and efficiency in the travel industry, and many others.
You will need access to the following;
The architecture looks like this:
These steps are depicted in the diagram below:
The first step is to set up Amazon Connect’ SDK, amazon-connect-streams, along with the connect-rtc-js library. This was already covered in a previous post, building an AI Travel Agent using Symbl.ai’s Nebula LLM and Amazon Connect . The rest of this post assumes that you have access to both customer and agent audio streams from the web application.
Afterwards, start by generating a unique identifier as follows:
We use this generated connectionId for connecting to Symbl.ai Streaming API in order to get customer and agent transcriptions for a given session. The process goes like this:
With this in place, we call the function 2 times, one for each user, passing the same connectionId so they join to the same connection.
Now let’s see how to assist the agent during calls in real-time. We do this in the handleMessage that we binded to the onMessage event listener as follows:
The sendToNebula function concatenates all the messages of the user into an array of messages called messagesFromSymbl. We then send that single array to Nebula using the callNebulaStreaming function which we will describe later.
Now let’s take a look at the callNebulaStreaming function:
You can find more info about Nebula API in the Nebula Chat reference page.
When the call ends we call nebula to provide us with the summary of the conversion. The flow is the same as the callNebulaStream() function but now with a single message and a different system_prompt for gathering summaries:
You’ve seen how these powerful Generative AI tools can be harnessed to redefine the standards of customer interaction, agent assistance, and post-call analysis. If you’re ready to empower your agents with unparalleled insights and efficiency, contact the integration experts at WebRTC.ventures today!