2. Developer challenges
Conversational interfaces need to combine a large number of
sophisticated algorithms and technologies
Speech
recognition Language
understanding
Business logic
Disparate
systems
Authentication
Messaging
platforms
Scale Testing
Security
Availability
Mobile
4. Amazon Lex – Features
Text and speech language understanding: powered by the same
technology as Amazon Alexa
Deployment to chat services
(Web/Mobile Apps, Facebook, Kik, Slack, Twilio SMS)
Designed for builders: efficient and intuitive tools to build
conversations; scales automatically
Versioning and alias support@
6. AWS Mobile Hub integration
Authenticate users
Analyze user behavior
Store and share media
Synchronize data
More ….
Track retention
Conversational bots
Amazon LexAWS Mobile SDKs
AWS Mobile Hub
7. Versioning and alias support
AliasVersioning
• Supported for intents, slots, and bots
• Enables multideveloper environment
• Rollback to previous versions
• Deploy different aliases to different platforms
• Run different stacks for dev, stage and prod environments
• Target different user groups with different aliases
v1 v2 v3 latest
v1 Dev
v2 Stage
v3 Prod
8. Amazon Lex use cases
Informational Bots
Chatbots for everyday consumer requests
Application Bots
Build powerful interfaces to mobile applications
• News updates
• Weather information
• Game scores …
• Book tickets
• Order food
• Manage bank accounts …
Enterprise Productivity Bots
Streamline enterprise work activities and improve efficiencies
• Check sales numbers
• Marketing performance
• Inventory status …
Internet of Things (IoT) Bots
Enable conversational interfaces for device interactions
• Wearables
• Appliances
• Auto …
9. Amazon Lex
Utterances
Spoken or typed phrases that invoke
your intent
BookHotel
Intents
An intent performs an action in
response to natural language user
input
Slots
Slots are input data required to fulfill
the intent
Fulfillment
Fulfillment mechanism for your intent
10. “Book a hotel”
Book hotel
NYC
“Book a hotel in
NYC”
Automatic speech
recognition
Hotel booking
New York City
Natural language
understanding
Intent/slot
Model
UtterancesHotel Booking
City New York City
Check in Nov 30th
Check out Dec 2nd
“Your hotel is booked for
Nov 30th”
Amazon Polly
Confirmation: “Your hotel
is booked for Nov 30th”
“Can I go ahead
with the booking?
a
in
11. Utterances
I’d like to book a hotel
I want to make my hotel reservations
I want to book a hotel in New York City
Can you help me book my hotel?
12. Slots
Destination City New York City, Seattle, London …
Slot Type Values
Check in Date Valid dates
Check out Date Valid dates
13. Slot elicitation
I’d like to book a hotel
What date do you check in?
New York City
Sure, what city do you want to book?
Nov 30th Check in
11/30/2017
City
New York City
14. Amazon Lex – technology
Amazon Lex
Automatic Speech
Recognition (ASR)
Natural Language
Understanding (NLU)
Same technology that powers Alexa
Amazon Cognito CloudTrail CloudWatch
AWS Services
Action
AWS Lambda
Authentication
& Visibility
Speech
API
Language
API
Fulfillment
End Users
Developers
Console
SDK
Intents,
Slots,
Prompts,
Utterances
Input:
Speech
or Text
Multi-Platform Clients:
Mobile, IoT, Web,
Chat
API
Output:
Speech (via Amazon Polly TTS)
or Text
21. Tens of thousands of Customer Service Associates support Amazon
customers around the world.
Amazon strives to be
Earth’s most customer-centric company
AMAZON
SUPPORTS
Millions Of Customers
Dozens Of Languages
32 Countries
22. Real time and
historical analytics
Skills-based routing
[Automatic Call Distribution (ACD)]
Call
recording
High-quality
voice capability
Easy to use, cloud-based contact center solution that scales
to support businesses of any size
With Tools That Grow With Your Needs
Amazon Connect
23. Turn Months Into Minutes
Self-service setup with just a few easy steps
before you take your first call
24. NATURAL
Amazon Lex Chatbots
use the same technology
that powers Alexa
DYNAMIC
Answer customer
questions before they
are even asked
PERSONAL
Contact flows adapt on
a per customer basis
Ok, you are now
booked for a
9:00AM departure
tomorrow out of
San Francisco,
arriving in Seattle
at 11:45AM.
Can you
please
rebook me
for the
same flight
tomorrow?
Great
Thank you!Data
Dip
CRM
content
Hi Nikki Wolf,
I see your flight
was cancelled
today. How can
I help you?
Incoming
customer
call
Contact Flow Engine – Customer Experience
25. OPEN PLATFORM
Your
S3 Storage
Your Data
Warehouse
Customer
Databases
Business
Intelligence
Workforce
ManagementAgent Data
AWS
Lambda
Call
Recordings
Metrics
Contact
Flows
CRM Contact
Control Panel
Open Platform/ Easy Integrations
41. Summary of Configuration
Queues
• Agent1Queue
• Agent2Queue
• Team1Queue
On each queue, set an outgoing
number dedicated to individual
users.
Amazon
Connect
Working Profiles
• Agent1Profile
• Agent1Queue
• Team1Queue,
• Set the outgoing queue to
Agent1Queue.
• Agent2Profile
• Agent2Queue
• Team1Queue
• set the outgoing queue to
Agent2Queue.
Users
• Agent1
• Agent2
42. Summary
• Conversational interfaces built with Amazon Lex
• Call Centre running on Amazon Connect
• Voices provided by Amazon Polly
• Business logic built in AWS Lambda
• Extend this, for example:
• Integrate the bot with text based services such as Slack, Twilio
• Call Recordings Stored in S3 – audit and analysis
• Integrate with CRM tools
• Click to dial from Salesforce