SPEAKER 1: Let's now take
a look at a demo of
Microsoft and Aisera's AI Co-Pilot.
We will cover three use cases.
In the first use case,
our focus will be the IT domain,
leveraging Aisera's IT specific large language models.
In this use case,
we will highlight the following.
Integration with Microsoft Teams,
where the users collaborate and
it becoming the system of engagement.
We will then demonstrate the ability
to understand the intense from
an ambiguous question and have human-like conversations
to fulfill the request without
the need for human intervention.
Taking it a step further,
we will then showcase Aisera's integration with
Microsoft Intune Endpoint Manager to assess
laptop issues and recommendation
of a solution to resolve the issues.
Let's begin. Here the user Rod Welsh begins by
asking an ambiguous question
around his laptop having issues.
The AI Co-Pilot then quickly understands the intent of
the question and offers
commonly found issues with laptop and Acme Corporation.
This demonstrates the ability for
the understanding of
ambiguous questions and the ability to
now recommend problem areas based on
what the Co-Pilot has learned in
Acme Corporation from other users.
But Rod Welsh has a different issue and starts
to specify more details
that his computer is running slow.
The AI Co-Pilot quickly recognizes Rod from
his profile based on his credential in Active Directory,
and learns that he is using a Windows PC.
It then asks for confirmation of his laptop.
The AI Co-Pilot then analyzes his laptop using
Microsoft Intune in the background and
lets him know the various applications running on it.
Microsoft PowerPoint, Google Chrome,
Citrix Workplace, Microsoft Outlook.
Aisera then advises on
the applications consuming the most CPU, in this case,
Citrix Workspace and Outlook,
and recommends terminating both applications.
However, Rod decides to terminate Outlook.
The IA Co-Pilot then terminates
Microsoft Outlook and checks
again on the health of Rod Welsh's computer.
This time it recognizes that
the CPU usage has gone down by
35 percent and asks Rod if the issue has been resolved.
Rod then confirms the issue has been resolved.
As you can see from this use case,
the AI Co-Pilot was able to not
only converse in a human-like fashion with Rod,
but also fulfill this request
without the need for a human agent.
It understood the intent of an ambiguous question,
provided recommendations from what it has learned from
other users that are
likely to be the causes of the problem,
and then leverages its integrations
like Microsoft Intune to remedy the issue.
Now let's look at use case number 2.
This use case also focuses on
the IT domain and helps Rod Welsh,
a manager at Acme Corporation to onboard a new employee.
We will build on top of the capabilities already
demonstrated for the Co-Pilot and in this use case,
we will demonstrate additional capabilities
like proactive notifications for a pending task.
Let's begin from where we left off.
Now, the AI Co-Pilot notifies
Rod Welsh that he has to onboard a new employee,
Mark Smith, so Rod starts the onboarding process.
To begin the process,
the AI Co-Pilot asks Rod to
select a buddy for Mark and offers
a drop-down menu of people that are
the likely choices for Mark
based on the organization he will be joining.
Rod selects Georgette Kramer and moves to the next step.
The AI Co-Pilot then asks
Rod if he would like to kick off the standard or
custom onboarding process while
displaying what the standard process recommends.
The standard process assigns
a few training programs like Acme Product Overview,
Sales Enablement, Sales Process at Acme Corporation,
and Company Onboarding programs.
It creates an e-mail,
an Okta profile, an Azure account,
and offers to provision access to SaaS applications like
salesforce.com, OpenVPN, and Outreach.
It also adds him to
the distribution lists that he is likely to join based on
Mark's profile in the organization
and highlights the standard computer available.
However, Rod decides to go
with the custom onboarding process instead.
The AI Co-Pilot now gives him the option to
modify his email address, Azure account name,
home shipping address, and
the ability to modify the laptop type,
but Rod leaves the selection unchanged and continues.
The AI Co-Pilot then asks
Rod which applications he would like to provision
that includes the standard onboarding options
of OpenVPN and a few new ones,
like Asana SAP,
ServiceNow, and Trello.
Mark selects all.
The AI Co-Pilot now gives Rod more options for
distribution lists and Rod selects
sales US-West and all company.
Finally, the Co-Pilot summarizes
all the selections made by
Rod Welsh for Mark Smith and asks to proceed further.
Mark clicks "Yes" and the AI Co-Pilot then completes
all individual tasks and
confirms with Rod that they've all been done.
It also generates an email to Mark Smith with
Day 1 instructions and CCs Rod Welsh.
This is the classic use case where
a manager is expecting a new employee
and based on the records of employment
through the integration of any EHR system,
the AI Co-Pilot proactively notifies
the manager of kicking off the onboarding process and
also recommends options based on
the new user's profiles for
the manager to make the right selections.
Now let's take a look at use case number 3.
Again, we will build on top of the capabilities already
demonstrated for the Co-Pilot in
use case number 1 and number 2.
Here, we will demonstrate additional capabilities like
understanding multi-intent questions, context switching,
the ability to remember conversation history,
and the fulfillment of all tasks from
external approved websites like
Microsoft support pages and internal knowledge sources.
Let's begin with where we left off.
Rod starts with a very long question and
the AI Co-Pilot quickly understands this question.
The AI Co-Pilot then
confirms with Rod the three intensive
detected and let him know
that they will be addressed one at a time.
The detected intense were
inviting external users to Microsoft Teams,
searching people in Microsoft Teams,
and creating group chats with coworkers.
Rod selects, inviting external users to
Microsoft Teams and the AI Co-Pilot then
quickly pulls up a resolution summary with
a link to Microsoft support page for more information.
It then asks Rod if that helped and Rod hits Yes.
The AI Co-Pilot now remembers that it still
had two more tasks or intents to be completed.
It then asks Rod for
which issue he would like to solve next.
Instead, this time,
Rod digresses from his original question
and asks another question with a different intent.
He asks for information on updating the name of
a private team channel that
was owned by a previous employee.
To respond, the AI Co-Pilot
then once again serves him with
a response summary from
the Microsoft support webpage
and asks if that resolved the issue.
Instead of hitting Yes or No,
Mark digresses once again and
asks how to connect his phone to Wi-Fi.
Note that campus here is misspelled,
but the AI Co-Pilot is still able to
understand that he needs to
connect to the company's Wi-Fi.
The AI Co-Pilot provides a resolution summary,
but this time it is from
Acme's internal knowledge source of service now.
The AI Co-Pilot then asks Rod if it helped,
and he responds by saying Yes.
Upon saying yes, the Aisera Co-Pilot reminds him of
the two unfulfilled tasks that were still
pending and if he would like to complete those.
This concludes the three use cases we wanted to
highlight for Microsoft and Aisera's AI Co-Pilot.
Thank you for joining us today.
If you have any questions,
please feel free to visit our website www.aisera.com.