Conversational AI interfaces add human-like conversation capabilities to your business applications by combining different natural language technologies like natural language processing (NLP), natural language understanding (NLU) and natual language generation (NLG). Conversational interfaces continue to grow as one of the preferred ways for users to interact with businesses. Covid-19 has further accelerated the adoption of these interfaces given social distancing rules and shelter in place orders. Enterprises are developing conversational interfaces to engage with users in new ways like interactive chatbots or virtual assistants capable of understanding customer needs, gathering required user information, and integrating back-end services to complete the required task.
With Amazon's Conversational AI (CAI) solutions, enterprises can use AWS AI Services or leverage AWS Partners' expertise to build highly effective chatbot and voice experiences, increase user satisfaction, reduce operational costs, and streamline business processes - all while speeding up time-to-market.
Enable new ways of engagement
Conversational AI allows you to engage with your customers in entirely new engaging ways like chatbots, voice assistants, interactive information kiosks and more across a variety of communication channels.
Increase customer satisfaction
Conversational AI interfaces provide omnichannel, self-service capabilities to customers 24/7. They can complete high-frequency tasks, provide and gatheri information faster and more conveniently for users.
Reduce operational costs
Conversational AI interfaces help deflect calls and reduce time-consuming interactions. In addition, they can streamline business processes by connecting with different back-end systems to complete the required tasks.
Streamline business processes
Conversational AI interfaces like chatbots and virtual assitants can help enterprises achieve their business goals faster and more efficiently. For example, enabling users to onboard faster, or book an appointment through a conversational interface.
Ryanair improves customer support using Amazon Lex
Using Amazon Lex and Amazon SageMaker, Ryanair built a chatbot that improves its customer support experience and helps customers find answers to their questions quickly and easily.
Saint Louis University Creates Chatbot Platform for Students
Saint Louis University (SLU) worked with AWS Professional Services on building a chatbot platform to improve student productivity and campus engagement. With the AskSLU chatbot, students are able to ask hundreds of questions about the university through a variety of modes—such as the SLU website, text message, and Amazon Echo devices across campus—and get the same response.
When the COVID-19 pandemic reached New York City in March 2020, Manhattan-based nonprofit insurer MetroPlusHealth and its more than 570,000 members found themselves in one of the epicenters. In partnership with AWS they used Amazon Lex to develop a chatbot that interacted with 54,000 members in the space of just 3 weeks, connecting New Yorkers with resources that addressed their physical, social, and emotional needs.
Use case categories
Provide information to customers through chatbots and voice assistants. For example, checking order status. These tend to be high volume, low complexity tasks.
Gather information from a user through a conversational interface. For example, on-boarding a new account, or booking an appointment.
Enable customers to complete a transaction via conversational AI. For example, transferring money or ordering a product or service.
Prompt the user with help, based on usage behavior through conversational AI. For example, helping a user who is having difficulty filling out a form.
Ready to get started?
Contact us for more information on AWS AI and Machine Learning solutions for Conversational AI solutions
Learn more about AWS CAI technology and consulting partners
Leverage Amazon AI Services to develop your own Conversational AI solution
Do it yourself
Amazon offers, among others, the following AI Services that can be used by your development team to create your own AI chatbots or virtual assistants.
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
Amazon Kendra is an intelligent search service powered by machine learning. Using Amazon Kendra, you can stop searching through troves of unstructured data and deliver the right answers to your customers through self-service chatbots, virtual agents, or IVR systems.
Amazon Polly is a service that uses advanced deep learning technologies to turn text into lifelike speech. With Amazon Polly, you can engage customers with natural sounding voices for your interactive voice response (IVR) systems, and chatbots. With dozens of lifelike voices across a broad set of languages, you can build a self-service customer experience that works in many different countries.
You can use the following AWS Solutions Reference Architectures as a reference.
AWS Solutions Reference Architectures are a collection of architecture diagrams, created by AWS. They provide prescriptive guidance for applications, as well as other instructions for replicating the workload in your AWS account.
This reference architecture deploys a multi-channel, multi-language conversational interface (chatbot) that responds to customer’s questions, answers, and feedback.
Reference architecture for implementing sophisticated conversational chatbots and developing engaging and lifelike experiences for your customers.