Curious Bot

Antonio Savasta – Matteo Finistauri

AI&RPA Lead Manager – AI Tech Architect and Team leader

VIRTUAL AGENT

An accelerator for conversational bot implementations

Overview CuriousBot 4.0

Market-leading companies use Artificial Intelligence (AI) to build their Digital Workforce

Integration Service (RPA and Application Integrators)

Automated

execution of routine

processes

Robotic

Process

Automation

“No touch”

approach

Automated

processing of

unstructured

documents

Natural

Language

Processing

Document and

communication

classification

Automated

customer

interactions and

internal support

Digital

Assistants

Automating

routine front-end

interactions

Automated learning

Machine

Learning

Automated and

semi-automated

data analysis and

insight mining

Smarter decision

making and KPIs

Expert

Systems and

Analytics

Operational

decision

optimization

Automated

processing of

images and visual

inputs

Computer

Vision

Analyzing and

classifying Images

Company

Bot Plattform

IT Bot

• Helpdesk

• Tickets

• Q&A

• WLAN Access

• Orders

Product Bot

• Product information

• Service questions

• Q&A

Sales Bot

• Assistant

• CRM Infos

• Voice Frontend

• Product Information

Service Bot

• Sparepart Info

• Product Info

• Voice Frontend

• Time Booking

Compliance Bot

• QM

• Org Info

Knowledge Bot

• Voice Frontend

• Topic Information

• Search Integration

….. B

ot

Ad

vis

ory

Tech

no

log

y B

riefi

ng

, B

usi

ness

Im

pact

& C

ase

s

Based on CuriousBot

Delivery Model (Planning, Support, Marketing, Training, …)

Change Management (Communication, Training, Culture)

Ru

n B

ot‘

s(R

un

an

dle

arn

org

an

isati

on

)

Bot StrategyThe Bot Strategy

creates the base for a

solid development of a

voice portal to your

company and

processes. It shows the

way in which thematic

areas are integrated

one after the other.

Chatbots are divided

into a continuous

landscape and ensure

thereby a solid

operability of the

solution.

Avanade sees chatbots as part of a sustainable bot strategy

CuriousBot Architecture & Main Features

Digital Agent

Azure Web App or Bot Service

High Level Architecture of a Bot based on Microsoft Bot Framework

…

Telegram

Email

Messenger

GroupMe

Skype

Slack

SMS

Web

Additional Channels

Node js or .Net Chatbot Web Application

Bot Connector

EndPoint

Bot Builder SDK

Cognitive API’s and

AI Services

Speech VisionLanguage

Machine

Learning

Cognitive

Services

Knowledge Search

Backend Systems and Services Authentication

MS Teams

Avanade

CuriousBot

Bot Service can be deployed

in any Cloud or on-premises

Alternative Services

can be integrated,

e.g. DeepL

Translation

CuriousBot as accelerator for chatbot implementation

Spell Check

Reporting

Configurable LUIS Integration Multi-lingual

Prepared for Machine Learning

Optimizeddecision ranking

RPA preparedEmotion

Input channels

Cognitive Services

Recommendations

Knowledge Exploration

Entity Linking

Academic Knowledge

QnA Maker

Custom Decision

Bing Autosuggest

Bing Image Search

Bing News Search

Bing Video Search

Bing Web Search

Bing Custom Search

Bing Entity Search

Translator Text

Bing Spell Check

LUIS

Web Language Model

Text Analytics

Linguistic Analysis

Bing Speech

Translator Speech

Speaker Recognition

Custom Speech

Computer Vision

Face

Content Moderator

Emotion

Video

Custom Vision

Video Indexer

Dialogue Layer

Perception Layer

How do CuriousBot and Microsoft Cognitive Services work together Machine Learning & Knowledge Base Layer

Bing Speech

Text Analytics

QnA Maker LUIS

TranslationChat

History

Crawler Process

Knowledge Bases

Decision Logic

Response Generator

Bing Speech Translation

pass to Bing Search results

Other actions:

request to ticket system

pass to Self Service Portal

Model Training

Dialog data flow

Emotion data

Avanade´s CuriousBot further enhances Microsoft´s bot framework´s potential in three additional ways

Dialogue Configurability Intelligent Decision Making On-Premises Infrastructure

Dialogues within a bot solely based on Microsoft

Bot Framework must be created, altered and

deleted directly in the source code.

There is no direct configuration capability for

the dialogue flow.

By default the Microsoft Bot Framework is not

offering intelligent decision when using cognitive

services. It provides building blocks, but not a

ready-to-use solution.

Combination of multiple Cognitive Services such

as LUIS and QnAMaker requires programming

and advanced experience.

The standard approach of Microsoft Bots is

completely cloud-based with the option of a

hybrid setup for the core bot logic.

A pure on-premises solution is not possible out-

of-the box. Custom programming is required to

keep sensitive bot dialogues on-premises, and

use Cognitive Services only in an anonymized

manner.

Our Management Application provides user-friendly bot configuration

Editing dialogue steps, adding and editing QnAs, adding utterances and training LUIS models can be done within our central management application which is easily accessible via the browser.

User Frontend

Example of a graphical Chatbot integration (Screenshots)

User Interface

“Ask Anna“ is just one example

of the elegant and smart

integration of a chat bot into

any website.

Together with our UX

department, a group of user

guidance and design

professionals from the agency

sector, we support customers in

developing further concepts

and implementations.

Example scenario for CuriousBot: Office 365 FAQ

ContinentalBot Use Cases

Generalist SpecialistIT Knowledge

Fast SlowSolution Speed

Low HighSupport Costs

High LowUser Satisfaction

Chatbot supported

self helpService Desk (1st Level) 2nd Level Support 3rd/4th Level Support

Use case, use case, use case – Do’s

• Realistic and impactful for the first bot

• Ideally, a task that every employee needs everyday

• Real KPIs against them with real timelines for ROI

• It has to be simpler, easier & faster with the bot than any other option

Use case, use case, use case – Dont’s

• Throwing a bot at any problem won’t solve it successfully

• Is Conversation the right approach for the use case?

• Solve a real problem, don’t implement a bot for the sake of having one

ContinentalTechnical Details

AZURE CLOUD

Why hybrid topology for CuriousBot?

Easy access to internal backend services

Single https connection from Azure to Bot Service

Easy authentication and control to backend systems

Local storage for anonymized chat history

No Cloud data storage required

Easy to convince Corporate Security

Backend SystemsCuriousBot

Chatbot central logic,

Chatbot landing page

Reverse Proxy

Bot Framework Connector

Connect to Chatbot

SQL

Firewall

User channel

Microsoft Cognitive Services

QnA Maker

LUIS

Text Analytics

Translation

Bing Speech

Emotion

Bing Search

DMZ & INTRANET

Frontend & Backend

Firewall

https / JSON

https / JSON

https / JSON

Concurrent LUIS and

QnAMaker analysis

Dialog Start

Welcome CardMO Greeting

User Input

Check FAQ(QnAMaker)

LUIS AnalysisLUIS Recognized

Answered?Problem

classification

SSP Request

TicketRequest

Show Best Responses

(carousel card)

Self Service Portal

request

Ticket request

Open Ticket

PostQuestion?

Core NWS

No

Write NWS and Confirm

Open Ticket and Confirm

Yes

Yes

Collect Feedback

No

Start Bing Search

Show Bing Search results (carousel card)

Answered?

Yes

NoYes

Yes

Nothing Recognized

Explain current scope

Cancel

I am learning<help info>

The chatbot leverages multiple knowledge sources

Managed Content

MO Productive QnA

MO QualityQnA

Content Management

App

O365 General

Questions

New Work Style Social

Support Forums

API

Crawler

Manual Import

User Interaction

A crawler continuously collects new knowledge

MO Production QnA

Quality CheckQnA

Approve/Modify via Management

App

New Work Style

Forums

Crawler Process

Upload

• Runs hourly• Reads only answered questions (V1)• Complete crawl

Metadata required:• Source• Modified timestamp• Forum• Answered flag• Approved flag• Synced flag• Answer-ID

Modify

Train/Publish

Manual tasks via Management App:• Check content• Format check• Approve

View filtered by:• Topic• New changes• Very old entries

to be reviewed

Post question

on social

support forum

‘Crowdsource

’ Knowledge

Don’t have an answer!

Hey MO!

What is…?

The answer

is: 42

Awesome!

Content management

Automatically

filled by Crawler

process

Used by MO bot

(QnAMaker)

Move. Edit

and Approve

Content

Chatbot management dashboard

Power BI reports for chatbot insights

MO - Continental

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