AWS Machine Learning Blog
Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center
This blog post is co-written with Bruno Mateus, Jonathan Diedrich and Crispim Tribuna at Talkdesk.
Contact centers are using artificial intelligence (AI) and natural language processing (NLP) technologies to build a personalized customer experience and deliver effective self-service support through conversational bots.
This is the first of a two-part series dedicated to the integration of Amazon Lex with the Talkdesk CX Cloud contact center. In this post, we describe a solution architecture that combines the powerful resources of Amazon Lex and Talkdesk CX Cloud for the voice channel. In the second part of this series, we describe how to use the Amazon Lex chatbot UI with Talkdesk CX Cloud to allow customers to transition from a chatbot conversation to a live agent within the same chat window.
The benefits of Amazon Lex and Talkdesk CX Cloud are exemplified by WaFd Bank, a full-service commercial US bank in 200 locations and managing $20 billion in assets. The bank has invested in a digital transformation of its contact center to provide exceptional service to its clients. WaFd has pioneered an omnichannel banking experience that combines the advanced conversational AI capabilities of Amazon Lex voice and chat bots with Talkdesk Financial Services Experience Cloud for Banking.
“We wanted to combine the power of Amazon Lex’s conversational AI capabilities with the Talkdesk modern, unified contact center solution. This gives us the best of both worlds, enabling WaFd to serve its clients in the best way possible.”
-Dustin Hubbard, Chief Technology Officer at WaFd Bank.
To support WaFd’s vision, Talkdesk has extended its self-service virtual agent voice and chat capabilities with an integration with Amazon Lex and Amazon Polly. Additionally, the combination of Talkdesk Identity voice authentication with an Amazon Lex voicebot allows WaFd clients to resolve common banking transactions on their own. Tasks like account balance lookups are completed in seconds, a 90% reduction in time compared to WaFd’s legacy system. The newly designed Amazon Lex website chatbot has led to a substantial decrease in voicemail volume as its chatbot UI seamlessly integrates with Talkdesk systems.
In the following sections, we provide an overview of the components that have this integration possible. We then present the solution architecture, highlight its main components, and describe the customer journey from interacting with Amazon Lex to escalation to an agent. We end by explaining how contact centers can keep AI models up to date using Talkdesk AI Trainer.
The solution consists of the following key components:
- Amazon Lex – Amazon Lex combines with Amazon Polly to automate customer service interactions by adding conversational AI capabilities to your contact center. Amazon Lex delivers fast responses to customers’ most common questions and seamlessly hands over complex cases to a human agent. Augmenting your contact center operations with Amazon Lex bots provides an enhanced customer experience and helps you build an omnichannel experience, allowing customers to engage across phone lines, websites, and messaging platforms.
- Talkdesk CX Cloud contact center – Talkdesk, Inc. is a global cloud contact center leader for customer-obsessed companies. Talkdesk CX Cloud offers enterprise scale with consumer simplicity to deliver speed, agility, reliability, and security. As an AWS Partner, Talkdesk is using AI capabilities like Amazon Transcribe, a speech-to-text service, with the Talkdesk Agent Assist and Talkdesk Customer Experience Analytics products across a number of languages and accents. Talkdesk has extended its self-service virtual agent voice and chat capabilities with an integration with Amazon Lex and Amazon Polly. These virtual agents can automate routine tasks as well as seamlessly elevate complex interactions to a live agent.
- Authentication and voice biometrics with Talkdesk Identity – Talkdesk Identity provides fraud protection through self-service authentication using voice biometrics. Voice biometrics solutions provide contact centers with improved levels of security while streamlining the authentication process for the customer. This secure and efficient authentication experience allows contact centers to handle a wide range of self-service functionalities. For example, customers can check their balance, schedule a funds transfer, or activate/deactivate a card using a banking bot.
The following diagram illustrates our solution architecture.
The voice authentication call flow implemented in Talkdesk interacts with Amazon Lex as follows:
- When a phone call is initiated, a customer lookup is performed using the incoming caller’s phone number. If multiple customers are retrieved, further information, like date of birth, is requested in order to narrow down the list to a unique customer record.
- If the caller is identified and has previously enrolled in voice biometrics, the caller will be prompted to say their voice pass code. If successful, the caller is offered an authenticated Amazon Lex experience.
- If a caller is identified and not enrolled in voice biometrics, they can work with an agent to verify their identity and record their voice print as the password. For more information, visit the Talkdesk Voice Biometric documentation.
- If the caller is not identified or not enrolled in voice biometrics, the caller can interact with Amazon Lex to perform tasks that don’t require authentication, or they can request a transfer to an agent.
How Talkdesk integrates with Amazon Lex
When the call reaches Talkdesk Virtual Agent, Talkdesk uses the continuous streaming capability of the Amazon Lex API to enable conversation with the Amazon Lex bot. Talkdesk Virtual Agent has an Amazon Lex adapter that initiates an HTTP/2 bidirectional event stream through the StartConversation API operation. Talkdesk Virtual Agent and the Amazon Lex bot start exchanging information in real time following the sequence of events for an audio conversation. For more information, refer to Starting a stream to a bot.
All the context data from Talkdesk Studio is sent to Amazon Lex through session attributes established on the initial ConfigurationEvent. The Amazon Lex voicebot has been equipped with a welcome intent, which is invoked by Talkdesk to initiate the conversation and play a welcome message. In Amazon Lex, a session attribute is set to ensure the welcome intent and its message are used only once in any conversation. The greeting message can be customized to include the name of the authenticated caller, if provided from the Talkdesk system in session attributes.
The following diagram shows the basic components and events used to enable communications.
Agent escalation from Amazon Lex
If a customer requests agent assistance, all necessary information to ensure the customer is routed to the correct agent is made available by Amazon Lex to Talkdesk Studio through session attributes.
Examples of session attributes include:
- A flag to indicate the customer requests agent assistance
- The reason for the escalation, used by Talkdesk to route the call appropriately
- Additional data regarding the call to provide the agent with contextual information about the customer and their earlier interaction with the bot
- The sentiment of the interaction
Talkdesk AI Trainer is a human-in-the-loop tool that is included in the operational flow of Talkdesk CX Cloud. It performs the continuous training and improvement of AI models by real agents without the need for specialized data science teams.
Talkdesk developed a connector that allows AI Trainer to automatically collect intent data from Amazon Lex intent models. Non-technical users can easily fine-tune these models to support Talkdesk AI products such as Talkdesk Virtual Agent. The connector was built by using the Amazon Lex Model Building API with the AWS SDK for Java 2.x.
It is possible to train intent data from Amazon Lex using real-world conversations between customers and (virtual) agents by:
- Requesting feedback of intent classifications with a low confidence level
- Adding new training phrases to intents
- Adding synonyms or regular expressions to slot types
AI Trainer receives data from Amazon Lex, namely intents and slot types. This data is then displayed and managed on Talkdesk AI Trainer, along with all the events that are part of the conversational orchestration taking place in Talkdesk Virtual Agent. Through the AI Trainer quality system or agreement, supervisors or administrators decide which improvements will be introduced in the Amazon Lex model and reflected in Talkdesk Virtual Agent.
Adjustments to production can be easily published on AI Trainer and sent to Amazon Lex. Continuously training AI models ensures that AI products reflect the evolution of the business and the latest needs of customers. This in turn helps increase the automation rate via self-servicing and resolve cases faster, resulting in a higher customer satisfaction.
In this post, we presented how the power of Amazon Lex conversational AI capabilities can be combined with the Talkdesk modern, unified contact center solution through the Amazon Lex API. We explained how Talkdesk voice biometrics offers the caller a self-service authenticated experience and how Amazon Lex provides contextual information to the agent to assist the caller more efficiently.
We are excited about the new possibilities that the integration of Amazon Lex and Talkdesk CX Cloud solutions offers to our clients. We at AWS Professional Services and Talkdesk are available to help you and your team implement your vision of an omnichannel experience.
The next post in this series will provide guidance on how to integrate an Amazon Lex chatbot to Talkdesk Studio, and how to enable customers to interact with a live agent from the chatbot.
About the authors
Grazia Russo Lassner is a Senior Consultant with the AWS Professional Services Natural Language AI team. She specializes in designing and developing conversational AI solutions using AWS technologies for customers in various industries. Outside of work, she enjoys beach weekends, reading the latest fiction books, and family.
Cecil Patterson is a Natural Language AI consultant with AWS Professional Services based in North Texas. He has many years of experience working with large enterprises to enable and support global infrastructure solutions. Cecil uses his experience and diverse skill set to build exceptional conversational solutions for customers of all types.
Bruno Mateus is a Principal Engineer at Talkdesk. With over 20 years of experience in the software industry, he specializes in large-scale distributed systems. When not working, he enjoys spending time outside with his family, trekking, mountain bike riding, and motorcycle riding.
Jonathan Diedrich is a Principal Solutions Consultant at Talkdesk. He works on enterprise and strategic projects to ensure technical execution and adoption. Outside of work, he enjoys ice hockey and games with his family.
Crispim Tribuna is a Senior Software Engineer at Talkdesk currently focusing on the AI-based virtual agent project. He has over 17 years of experience in computer science, with a focus on telecommunications, IPTV, and fraud prevention. In his free time, he enjoys spending time with his family, running (he has completed three marathons), and riding motorcycles.