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Amazon Lex
What is Amazon Lex?
Use Amazon Lex to create conversational interfaces in your apps by using a fully managed artificial intelligence (AI) service with advanced natural language models. Chatbots, voice assistants, and virtual assistants are a few examples of conversational interfaces that are becoming more and more common.It provides easy integration of artificial intelligence (AI) that understands purpose, keeps context, and automates simple activities across multiple languages. Omnichannel conversational AI may be created and deployed in a matter of seconds without the need for expensive hardware or infrastructure. It facilitates data access, business logic execution, performance monitoring, and other tasks by integrating easily with other AWS services. There are no set-up costs or minimum payments with this service. When text and voice requests come through, you simply pay for them.
How does it Work?
Deep learning tasks such as speech recognition and language interpretation can be tackled with Amazon Lex’s fully managed service, driven by the same technology as Alexa. AWS Lambda and Amazon Lex work together to make it easy to retrieve and update data. It can be used on chat platforms, mobile apps, and IoT devices. Use the reports to monitor your bot’s performance metrics. Building, publishing, and monitoring bots are all made easier with Amazon Lex.
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Conversations
Accurate, high-quality voice synthesis and comprehension
Amazon Lex uses speech recognition and natural language processing technology to build a system that can understand spoken words. Amazon Lex uses the same known technology as Alexa. Amazon Lex is able to learn from a few sample utterances provided by the developer how users can express their intent. The spoken language understanding system decodes the user’s purpose using natural language speech and text input.
The management of context
While engaging in a conversation, it is necessary to keep an eye on the bigger picture. Using Amazon Lex’s native context management functionality does not necessitate writing any new code. Contexts can be used to perform related intents after the initial requirements are met. This new method makes it easier to design conversational interfaces for automated systems.
Audio support for 8 kHz telephony
The training of Amazon Lex on 8-kHz sampling rate audio has enhanced the accuracy of speech recognition for telephone applications. A conversational bot built with Amazon Lex can have better fidelity because of the 8 kHz capacity for phone speech interactions, such as through a contact centre application or helpdesk.
Multi-way conversation
Amazon Lex bots are capable of holding conversations with multiple stages. It is essential to keep in mind that after an intent has been identified, users will be prompted to provide the information that is essential for the intent to be carried out successfully (such as check-in date and number of nights). Amazon Lex makes it easy to design multi-turn dialogues for your chatbots so you can test different scenarios. Amazon Lex will take care of orchestrating the conversation by asking for the appropriate slot, and all you will need to do is list the slots/parameters that you want to collect from the people that use your bot.
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Productivity of the Builder
Enormous Lifecycle Management Powers
Amazon Lex has a versioning option for the Intents and Bots you create. Versioning and rollback methods make it easier to keep track of code in a multi-developer environment. It is possible to create multiple aliases for Amazon Lex bots, each of which can be linked to a different version of the bot. To release new versions of the bot with your most recent updates and improvements, use this alias. There is no longer a requirement to re-update all of the clients when a new version of the bot is deployed.
As many platforms as you want with a single click.
Instead of building for each platform independently, you may publish your bot to chat services directly from the Amazon Lex interface. Chat platforms like Facebook Messenger, Slack, and Twilio SMS have a natural user experience because of their rich formatting possibilities.
Console performance has been improved.
Create, deploy, and manage conversational interactions with ease with the Lex V2 console. Because of Lex V2, a bot can have as many languages as it needs during the design, testing, and deployment phases of its lifecycle, all of which can be treated as a single resource. A reduced information architecture makes it easier to handle both versions. A ‘Conversation Flow,’ the option to save partially constructed bots, and the ability to upload utterances in bulk shorten the process and allow you to be more flexible in your use of the service.
Conversations being streamed
Pauses and interruptions interrupt and disrupt the natural flow of dialogue. When paying a bill by phone, a caller may ask to pause or hold the discussion while they look for the necessary information before answering a query about providing credit card information. streaming conversation APIs allow you to save time and effort by pausing a conversation and dealing with interruptions as you customize the bot. Using the correct technologies, virtual contact centre employees or smart assistants’ conversational abilities can be quickly improved.
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Integrations between AWS services
Integration with the Amazon Kendra platform
Frequently, customer support conversations revolve around locating specific information in order to answer specific queries, which can be frustrating for customers. Amazon Kendra is an intelligent search engine powered by machine learning that is both highly accurate and incredibly easy to use. Include a Kendra search purpose in your question to find the most accurate answers from unstructured documents and FAQs. In order to enhance the bot’s ability to gather information, simply include search index criteria in the intent when creating the bot.
Amazon Polly is integrated into the system.
Through the use of Amazon Polly, you can turn text into natural-sounding voice for use in your apps and products, as well as develop entirely new categories of speech-enabled products. As long as your customers are speaking, you can use Polly to answer. As part of Amazon Polly, the service now offers Neural Text-to-Speech (NTTS) voices, which use a revolutionary machine learning approach to speech recognition to increase speech quality.
Integration with Amazon Web Services Lambda
Data retrieval, updates, and business logic execution are all native to the cloud computing platform thanks to Amazon Lex and AWS Lambda integration. Allows for the seamless implementation of business logic at scale while you remain in control of the environment while you focus on designing bots. Your existing corporate applications and databases can be readily interfaced using AWS Lambda. For AWS Lambda, you only need to create your integration code and it will automatically be executed when data is provided or received by the system from an external source Amazon DynamoDB, Amazon SNS, and other AWS services can be accessed through this interface.
Integrations with Contact Centers
Amazon Connect integration
Amazon Lex, AWS’ cloud-based contact centre, may be used by developers to build voice-based conversational bots that can respond to customer queries over the phone. You can integrate Amazon Lex into any call centre application thanks to the APIs.
Contact Center Intelligence from Amazon Web Services (AWS) integrations (CCI)
You may create self-service customer care virtual agents, informational bots, and application bots automatically and seamlessly with Amazon Lex, which is integrated to several AWS CCI partners. Amazon Lex partners include Genesys, 8×8, Xapp.ai, Clevy, Inference, UIPath, and VoiceWorx.ai.
Pricing
It is possible to include voice and text-based conversational interfaces into any application that uses Amazon Lex, a service that Amazon provides. With Amazon Lex, you only pay for the services you actually need. Neither a down payment nor a minimum payment is required. Conversations with Lex bots on Amazon Lex can take place in a variety of ways, from one-on-one engagements to continuous streams. Because of this interaction, each user input (voice or text) is considered as a single API call during the request and response interaction. All of the user inputs from numerous turns are handled in a single streaming API call if you’re engaging in a streaming conversation.
Use Cases
Financial Services: With AWS, financial institutions may stand out from the competition while also preparing for the problems of the future in the banking, payment, capital market, insurance, and capital markets industries sectors. A financial institution may use Amazon Lex to change the way it delivers customer service to keep up with the evolving needs of its customers. Pre-built solutions for your use case are available with Amazon Lex for Financial Services, ensuring a positive customer experience without sacrificing operational efficiency. It is possible to utilize pre-built chatbots to automate customer assistance interactions such as credit card payments and mortgage loan applications. Amazon Connect contact flows are coupled with pre-configured bots for financial industry use cases that are pre-configured with intents, sample utterances, and slot types.
Credit card and bank accounts are only a few examples of the services that can be provided by financial institutions.
Insurance: Insurance businesses can take use of AWS’s adaptable infrastructure to improve customer interactions and risk profiles. Insurers may quickly create new digital customer experiences for their customers when they use Amazon Lex to enhance their basic infrastructure and offer customized insurance solutions.
Pre-built solutions from Amazon Lex for Insurance allow you to develop experiences at scale and increase digital engagement. Customer interactions including claims processing, policy administration, premium payment, and insurance quotations can be automated using pre-programmed chatbots. Conversation flows, training data, and dialogue prompts that may be utilised in both voice and chat are included in bots created for specific purposes. If you can deliver client solutions faster while still making the most of your existing resources, your teams may be able to work on more difficult problems and build deeper relationships.
Claims processing, house and auto policies and life policies are just a few instances of policy management and claims.
Retail: Retailers can create unique customer experiences, improve revenue, and do all of this on a fast, scalable, and flexible cloud infrastructure thanks to Amazon Web Services (AWS). To let businesses experiment with new ideas and improve the efficiency of their operations by giving a dynamic conversational experience is what Amazon Lex is all about.
Amazon Lex for Retail provides pre-built solutions to ensure a consistent brand experience across multiple touchpoints and transform customer contact. Automated interactions like checking the order status, redeeming loyalty points, and locating a retail location can be delivered by pre-built chatbots. Prebuilt bots for retail use contain ready-to-use bot setup and sample business logic links. These technologies can be deployed in a contact centre (for example, Amazon Connect), on social media platforms (for example, Facebook Messenger), or in a mobile application to deliver a rich across all stages of a customer’s relationship.
A few examples are customer account administration, order processing, shipping, loyalty programmes, and retail shop cards.
Telecom: AWS has the most up-to-date and secure cloud infrastructure, the fastest innovation, and the most comprehensive telecom alliances in the industry. Telecom firms can benefit from Amazon Lex by streamlining service delivery and providing their clients with access to cutting-edge communication and media technology. Customers’ experiences are improved, and operational costs are reduced, thanks to Amazon Lex for Telecom’s pre-built solutions. Paying bills, debating offers and supervising installations are all part of this process. All the way from acquiring more data to checking user inputs and applying business logic are the pre-built bots that provide end-to-end conversation flows for telecom use case scenarios. Account management, mobile, internet, television, and business solutions are just a few of the many options available.
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