working of chatbots

1. Engaging and Useful
Chatbot

2. Chatbot:
Chatbot play important role because they
serve as a guiding factor for both the
brand and the users. Chatbots may be
used to give online service, place
purchases for clients, and help resolve
customer complaints. Once the goal has
been established, the organization may
concentrate on personalizing the bot's
communication pattern.

3. • Despite technology changing the way
of interaction, the need for
supportive bonds and conversation to
address queries and share thoughts
quickly is still considered to be vital.
• Chatbots are the main formula for
our rescue…!
• Several companies today are
investing in this conversation-based
platform to provide the users with
accurate information.
Chatbot (contd;)

4. General AI/ML Overview:

5. How our Chatbots work?
Our Chatbots need the following to respond to an user question:
• What (skill) is the user asking for? (Intent)
• Did the user mention any specific information? (Slots)
• What should the bot ask to get further details from the user?
(Dialog flow/Maintaining Context)
• How to fulfil the user request? (Action/Response/Fulfilment)

6. AI + SRE Ops:

7. AI + SRE case scenario -1
• User Utterance: “I am facing copy paste error”.
• Chatbot: “Please use the blue eraser icon to mitigate copy/paste issue”.
• User Utterance: “I don’t see blue eraser icon”.
• Chatbot: “Please enter caseid/documented”.
• Chatbot: “Your incident number ”INCxxxxx” is created and will be
assigned shortly”.
Intent
•Content Issue
Slots
•Caseid – AR-xxxx
•App – CAP-Console
•Priority- P1
Dialog flow
•Back and forth
communication
between bot and
user
Action/Fulfillment
•Bot provides final
results in the
form of a link
where case details
are already
entered and
submitted.

8. AI + SRE case scenario -3
• User Utterance: “Unable to upload docs in RPM”.
• Chatbot: “Hi, this Issue can be fixed on reposting the release message”.
• Chatbot : “Do you want to open a ticket for this”.
• User Utterance: “Yes”.
• Chatbot: “Please enter jobid”.
• Chatbot: “Your incident number ”INCxxxxx” is created and will be
assigned shortly”.
Intent
•RDR Issue
Slots
•Jobid – PFR-xxx2
•App – RPM
•Priority- P1
Dialog flow
•Back and forth
communication
between bot and
user
Action/Fulfillment
•Bot provides final
results in the
form of a link
where case details
are already
entered and
submitted.

9. AI + SRE case scenario -2
• User Utterance: “I can't seem to find ESG section on PR”.
• Chatbot: “Please go to Section manager and enable ESG section”.
• User Utterance: “Section Manager is disabled, can’t click”.
• Chatbot: “Please enter caseid/documented”.
• Chatbot: “Your incident number ”INCxxxxx” is created and will be
assigned shortly”.
Intent
•Content Issue
Slots
•Jobid – PFR-xxx2
•App – RPM
•Priority- P1
Dialog flow
•Back and forth
communication
between bot and
user
Action/Fulfillment
•Bot provides final
results in the
form of a link
where case details
are already
entered and
submitted.

10. Chatbot Program Workflow:
Read csv / Snow
SVM/CNN
TF/IDF vectorization
Lemmatization
Accuracy check
Stop words removal
Feature Selection
Extraction
AWS
Update CSV/.dat

11. Chatbot classification used for Intent prediction:
Support Vector Machine (SVM)
• SVMs maximize the margin around
the separating hyperplane.
A.k.a. large margin classifiers
• The decision function is fully
specified by a subset of training
samples, the support vectors.
• Solving SVMs is a quadratic
programming problem
• Seen by many as the most
successful current text
classification method*
Support vectors
Maximizes
margin
Narrower
margin

12. Sample Python Bot interaction: