Easily migrate your IVR flows to Amazon Lex using the IVR migration tool

This post was co-written by John Heater, SVP of the Contact Center Practice at NeuraFlash. NeuraFlash is an Advanced AWS Partner with over 40 collective years of experience in the voice and automation space. With a dedicated team of conversation designers, data engineers, and AWS developers, NeuraFlash helps customers take advantage of the power of Amazon Lex in their contact centers.

Amazon Lex provides automatic speech recognition and natural language understanding technologies so you can build sophisticated conversational experiences and create effective interactive voice response (IVR) flows. A native integration with Amazon Connect, AWS’s cloud-based contact center, enables the addition of a conversational interface to any call center application. You can design IVR experiences to identify user requests and fulfill these by running the appropriate business logic.

Today, NeuraFlash, an AWS APN partner, launched a migration tool on AWS Marketplace that helps you easily migrate your VoiceXML (VXML) IVR flows to Amazon Lex and Amazon Connect. The migration tool takes the VXML configuration and grammar XML files as input and provides an Amazon Lex bot definition. It also supports grammars and Amazon Connect contact flows so you can quickly get started with your IVR conversational experiences.

In this post, we cover the use of IVR migration tool and review the resulting Amazon Lex bot definition and Amazon Connect contact flows.

Sample conversation overview

You can use the sample VXML and grammar files as input to try out the tool. The sample IVR supports the following conversation:

IVR: Welcome to ACME bank. For verification, can I get the last four on SSN on the account?

Caller: Yes, it’s 1234.

IVR: Great. And the date of birth for the primary holder?

Caller: Jan 1st 2000.

IVR: Thank you. How can I help you today?

Caller: I’d like to make a payment.

IVR: Sure. What’s the credit card number?

Caller: 1234 5678 1234 5678

IVR: Got it. What’s the CVV?

Caller: 123

IVR: How about the expiration date?

Caller: Jan 2025.

IVR: Great. How much are we paying today?

Caller: $100

IVR: Thank you. Your payment of $100 on card ending in 5678 is processed. Anything else we can help you with?

Caller: No thanks.

IVR: Have a great day.

Migration tool overview

The following diagram illustrates the architecture of the migration tool.

You can access the migration tool in the AWS Marketplace. Follow the instructions to upload your VXML and grammar XML files.

The tool processes the input XML files to create an IVR flow. You can download the Amazon Connect contact flow, Amazon Lex bot definition, and supporting grammar files.

Migration methodology

The IVR migration tool analyzes the uploaded IVR application and generates an Amazon Lex bot, Amazon Connect flows, and SRGS grammar files. One bot is generated per VXML application (or VXML file). Each input state in the VXML file is mapped to a dialog prompt in the Amazon Lex bot. The corresponding grammar file for the input state is used to create a grammar slot. For the Amazon Connect flow, each VXML file maps to a node in the IVR flow. Within the flow, a GetCustomerInputBlock hands off the control to Amazon Lex to manage the dialog.

Let’s consider the following VXML content in the sample dialog for user verification. You can download the VerifyAccount VXML file.

In addition to the preceding VXML file, we include the following SRGS grammars from the IVR application in the IVR migration tool:

last4SSN.grxml – Grammar to recognize the last four digits of the Social Security number
dateOfBirth.grxml – Grammar to recognize the date of birth

An Amazon Lex bot is created that to verify the caller. The Verification bot has one intent (VerifyAccount).

The bot has two slots (SSN, DOB) that reference the grammar files for the SSN and date of birth grammars, respectively. You can download the last4SSN.grxml and dateOfBirth.grxml grammar files as output to create the custom slot types in Amazon Lex.

In another example of a payment flow, the IVR migration tool reads in the payment collection flows to generate an Amazon Lex bot that can handle payments. You can download the corresponding Payment VXML file and SRGS grammars.

In addition to the preceding VXML file, we include the following SRGS grammars from the IVR application in the IVR migration tool:

creditCard.grxml – Grammar to recognize the credit card number
creditCardExpiration.grxml – Grammar to recognize the date of birth
creditCardCVV.grxml – Grammar to recognize the CVV on the credit card
paymentAmount.grxml – Grammar to recognize the payment amount

An Amazon Lex bot is created to collect the payment details. The Payment bot has one intent (MakePayment).

The bot has four slots (credit card number, expiration date, CVV, payment amount) that reference the grammar file. You can download the creditCard.grxml, creditCardExpiration.grxml, creditCardCVV.grxml, and paymentAmount.grxml grammar files as output to create the custom slot types in Amazon Lex.

Lastly, the migration tool provides the payment IVR contact flow to manage the end-to-end conversation.

Conclusion

Amazon Lex enables you to easily build sophisticated, natural language conversational experiences. The IVR migration tool allows you to easily migrate your VXML IVR flows to Amazon Lex. The tool provides the bot definitions and grammars in addition to the Amazon Connect contact flows. It enables you to migrate your IVR flows as is and get started on Amazon Lex, giving you the flexibility to build out the conversational experience at your own pace.

Use the migration tool on AWS Marketplace and migrate your IVR to Amazon Lex today.

About the Authors

John Heater has over 15 years of experience in AI and automation. As the SVP of the Contact Center Practice at NeuraFlash, he leads the implementation of the latest AI and automation techniques for a portfolio of products and customer solutions.

Sandeep Srinivasan is a Product Manager on the Amazon Lex team. As a keen observer of human behavior, he is passionate about customer experience. He spends his waking hours at the intersection of people, technology, and the future.