Intro to AI Agents
Check out this on demand webinar digging into the basics of Kustomer's AI Agents
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[silence]
Hello everyone and welcome.
We're so glad you're here for today's webinar on how AI agents are transforming
the customer support experience.
I'm Caroline Dangson, a product marketer, a customer, and I'll be your
moderator today.
Just a bit of housekeeping before we dive in, we'll be using the Q&A tool here
in Zoom webinars
to catch your questions and answer them as we go.
So please pop your questions into the Q&A tool instead of chat so we can keep
everything organized.
After the event, we'll send you the presentation slides and recordings so you
don't have to worry about taking notes.
And if you could just spare a moment to complete the quick survey at the end of
today's session, we'd really love to hear your feedback.
And thank you, let's get started.
AI agents are all the buzz in customer experience right now, and we're excited
to show you how customer offers them natively in our platform today.
So let's start, we're going to start by breaking down what AI agents actually
are and explore some real-time use cases in customer service.
Let me make sure I am sharing the presentation.
Great, so now you can see the agenda.
So we're going to start down again, like I said, what AI agents, what they are
and explore some real-time use cases.
Then we're going to show you them in action with a few demos and we'll wrap
things up with the Q&A.
So let's launch a poll.
We'd like to keep this interactive.
And we'd love to know from our audience today, what are you most excited to
learn about?
So are you excited to learn about how AI agents work?
How AI agents can improve the customer experience?
Maybe you are a customer of ours and you just want to check out what's new.
Anything else?
Other than that, let us know and answer in the chat.
So we're going to let people complete the poll before we show the results.
Great, so we have a lot of folks who are here to see how AI agents can improve
the customer experience,
which is perfect because that's right on topic.
They also have people who want to know how AI agents work.
So we are here to show you both of those.
And thanks to our customers who joined today as well.
So just two weeks ago, customer relaunched with AI completely integrated into
our platform.
This was a really big deal in milestone for our company.
For us, it was important that AI is built in and not bolted on.
And what this means is we are looking to unlock the full potential of our
platform from data,
AI agents, human agents to fully deliver on exceptional customer experiences.
And when you get to know the customer platform, our strategic advantage is the
data, the AI agents and the channels,
they're all native to our platform.
That was really important for us.
And that means that customers of ours can deliver faster, more efficient
customer service
and have more streamlined interactions with their customers based on having it
all readily available from one place.
Plus, in addition to that, we offer an app's marketplace with APIs and webhooks
as well.
So you can easily connect customers to the rest of your tech stack.
And this is for data that might live outside of our platform, but still
necessary to service customers.
So altogether, this empowers our customers to deliver a customer support
experience that's connected, efficient and proactive.
So when you think about the brands that you interact with on a daily basis,
think about the ones that truly value customer experience.
We're really proud to say that we work with a lot of those.
This is our proud slide of customers and logos that we work with, the
innovative brands that really prioritize this level of customer obsessed
service.
And now I'm really excited to introduce two of my colleagues who work very
closely with our customers,
Paul Anderson and Erin Nelson.
These are in-house experts on AI agents and so excited to have them join to
talk to us and answer these questions.
So Paul brings over 20 years of experience in CX technology.
And he's seen a customer experience evolve from phone to chat to SMS and now to
the day where AI agents are working across these channels.
Erin's been with customer for about five years and he develops training
materials for our customers to get the most out of our platform.
So while they join the webinar, while they come on, I'd like to launch a poll
that we can start to talk through about implementing AI agents.
We would love to know from our audience where things stands in terms of what
companies who've joined today, what they're considering,
have, has your company used AI agents yet?
Yes, we're looking into it or not sure.
Welcome, Paul and Erin.
Thank you.
Thank you, Carolyn. I appreciate that. Oh, look at those results.
So we have, you know, as expected, things have moved so fast with AI. I mean,
just as we tracked it as a company,
we are aware that a lot of people are, you know, I guess like Paul and Erin,
you can speak to this,
but like where customers are in terms of the adoption curve and what they're
considering.
So we see like 29% of those who have told us that, yes, they are already using
AI agents, where 69%, you know,
they're still looking into it, considering this.
Anything you Paul or Erin, you'd add in terms of like just where adoption is
and usage of AI agents with customer service.
Well, I love what this is.
Yeah, I think, Carolyn, the one thing that, you know, you said evolution and I
think where we are with AI agents right now,
it's a revolution.
It is absolutely changing where we are. And you mentioned, I have 20 years of
experience in the space and that started out from, you know,
where we're phone and telephony and moving into email and moving into chat and
SMS and social and WhatsApp.
But I really see those are all different ways to communicate. This is truly,
you know, the AI agent and the AI realm is truly a different way to think about
CX and how you're going to be moving forward with it.
And I don't think it, like I said, I don't think it's just an evolution. It's a
revolution on how things are going to be done moving on into the future.
So I'll let you join in here, Erin, if you have anything to add on that.
Yeah, I just think it's really, it's interesting to me that our results here on
the poll are so split that we don't really have anybody who is unsure about
where they stand on AI.
And I think that's very telling about where the market is and where we're
headed sort of as an industry.
Cole Paul, do you want to maybe kick it off and we'll get into the content
around.
So we all are on the same page about what are AI agents? Absolutely. And I
think as part of that, you know, your survey there, you know, people are really
trying to understand what AI agents are.
And it's a buzzword. You know, I used to do scuba diving and getting buoyant
and all these different types of things were buzzwords that everybody would
talk about.
And you know, what are AI agents? We're hearing it everywhere. We're reading
about it. We're seeing it. But what they are, it's just a, it's a software
program.
That can interact with environments differently that you give a set of
instructions to that can do different things that can reason can understand.
You know, when we think about AI agents, the humans are really building the
instructions in to the AI agent.
And then the AI agent could go off and independently do what they need to be
able to do.
So if you want to transition to the next slide there, Caroline, I think really
where we start to talk about this in a really interesting fashion is, you know,
we've all been in this world of the chatbots.
And, you know, we've been doing chatbots. We've become very familiar with it.
And that's been the last two or three years of where the CX space has gone.
And, you know, what is, you know, what is the difference between, you know, AI
chatbots and AI agents? We have a couple bullet points here.
But when you think about chatbots, you know, they stick to very specific
prompts.
They have, you know, basic decision making based upon just knowledge content.
Maybe they do simple generative AI capabilities, simple issue resolution.
But really that issue resolution is being driven by you on a path that you're
taking your customer down.
And it really just gives answers. There's no true action that occurs.
And like I said, where are we now in the evolution of AI and the evolution of,
you know, the ability to have a natural conversation with, you know, the
ability to have a natural conversation with, you know, the ability to have a natural conversation. With a particular, with an AI agent. So instead of saying, Hey, here's four
buttons. Pick what you want to do.
How can we help you Caroline today?
And have that AI agent understand that have advanced reasoning based upon data
from multiple sources. And I think Caroline did a fantastic job of
understanding and describing the customer platform.
And being able to layer this on top of all of that, our CEO likes to use this
word goodness. That's there. That can help you through these items.
You know, autonomously solving problems. And then, you know, I think at the end
of the day, it's all also about their situations where an actual human is going
to need to be involved.
And, you know, maybe we look out five years and seven years from now in AI
agents and AI can do everything. But in today's world, as Caroline talked about
earlier, and we're going to talk about more, you know, having the human in the
loop that that that individual where things can be escalated as necessary.
But like I said, this is a revolution in what's coming. And AI agents are, you
know, where we are as a company and where the future is going.
And, you know, I think I'm going to transition this over to Aaron right now and
we're going to do a short demo for you at the moment.
Yeah, before we go there, we've actually got some questions. I thought would be
interesting that are, you know, related to the slide. So that we might want to
address here.
And Aaron, feel free to jump in. But we have a question from Mercedes on how
does the AI feature know how to respond to certain questions? For example,
unable to install and want to return my order.
Great, great question Mercedes. And I think, you know, at the end of the day,
we're going to get into how you work with AI agents. And we have an acronym
internally of smart.
And one of the things that we talk about AI agents of being is specialized. And
that specialization allows them to be able to understand how to handle an item.
And, you know, I always think about this. I always like to put things in
context that maybe people understand, right? And if you've ever gone into a
best buy or a store, electronic store and you walk in and there's that person
at the front that says, Hey, what are you looking for today?
And maybe they have some general information about the business or they know
they sell TVs and appliances and computers. But when I come in and I say, Hey,
I want some really specific information about an 85 inch Samsung OLED TV.
That person goes, You know what, I have a team member that's going to be able
to help you with that. And I think you can think about AI agents as being a
members of a team that can help you in very specific situations.
And in your case, we'll talk about this in a few minutes, but is there some is
there an AI agent that's a damaged product expert? Is there an AI agent that's
a return expert? Is there a damn? Is there an AI agent that's an upsell expert?
Absolutely. And that's where you have this specialization amongst those. And we
'll describe that in a little bit more detail as we move forward.
And I would say we're about to show off in this demo the sort of natural and
human like way that agents can interact with our customers.
But to answer that question from Mercedes as well, how does the AI agent know
how to respond to certain questions? Just like any human agent, you tell them
when you get hired, you use language, you might write it down on a piece of
paper or something, but you are giving that information to the agent.
And that's what you are in charge of. And here is the scope of your
responsibilities. And you can do that again with natural language, which I just
think is incredible.
Yeah, yeah, let's let's, without further ado, let me let's get to that demo,
Erin. So let's maybe set that up. Yeah. So, like, start to talk about what we
're about to see.
Absolutely. It's not only do our agents respond and interact with natural and
human like language.
Something really cool that you'll see in this demo is that they can respond
using all of our native channels in customer and that includes voice, which is
the first demo we're going to show off here.
And we've prepared a little demonstration of an AI agent answering a phone call
. So let's take a look at that.
Awesome.
Hello, how can I assist you today?
Hi, I recently bought a sweater and I'm trying to figure out when it's going to
ship.
I need to verify your identity before we can proceed with your request. Could
you please let me know how you would like to receive the passcode for
verification? You can choose to receive it by your email or SMS.
SMS is fine.
I have sent a six digit verification code to your SMS. Please check your
messages and provide me with the code so I can verify your identity.
Your sweater order was placed on October 27, 2024 and it has been shipped. It's
expected to arrive by November 4, 2024. Do you need help with anything else?
No, that's it. Thank you.
You're welcome, Sydney. If you have any more questions in the future, feel free
to reach out, have a great day.
So in this demo, we saw a customer calling in about a purchase they made. They
were greeted by the AI agent and notice that this was a multi channel
conversation that was driven by the AI.
We had the agent interacting with the customer through voice, but it was also
smart enough to send a text message with a confirmation code. The customer is
able to use that and verify themselves so they could get the information they
were looking for.
And now I think I'd like to hand it back over to Paul to talk a little bit
about why we use AI agents.
Excellent. Wow. What an amazing demo. And I think seeing that in voice and
seeing that real time. And one of the things that if you've used customer or
you're familiar with customer, one of the big things we talked about is trust.
And you saw there that in Aaron's demo, we prompted for a verification code.
Similar can be done with unauthenticated chat transactions, SMS, email, any
transaction can be utilized a verification code to make sure that we are
talking to the person.
We're dealing with the person. So why is the team of AI agents better once
again, greater accuracy is we think about multiple agents. And as we chatted
earlier, I might have a return agent.
I might have a damaged product expert. I might have something that's out there,
you know, can cross verify information. And I think, you know, as we think
about having a set of team members.
And if you think about your contact center today, you have different people who
have different specialties within the contact center and you might have a tier
one, tier two, tier three.
You might also have specialist based upon specific skill sets that are working.
And I think about, you know, routing these conversations to the skill sets that
have the ability to handle them.
These AI agents also have the ability to collaborate together, which is an
amazing feat, the ability to say, and nobody, you know, I'd love to say
everybody that comes in with a question asks one question.
And, you know, if you want to throw a thumbs up out there, but people are
asking three or four questions in a single interaction with you.
And the ability for these AI agents to parse that information and understand it
and seamlessly pass it back and forth between the appropriate agents and skill
sets so they collaborate together.
Faster resolution, and we can talk about this as we get more into this, but
about teams and about the data that can be used in these interactions to be
able to do it.
And what's the right tools for those posts and going back to that best by
example of sending me over to the TV area.
That person has the right tools. They know about that television that I asked
about.
If I come in and ask about a refrigerator or a range, I go to the appliance
section and they have the information that's appropriate for that.
So the ability for them to faster resolve. If I went to the TV section and
asked about a refrigerator, it's really going to take me a long time to get my
answer.
So having that person that has the specialty associated to it.
And I ask, but not least, it's really about the maintenance of these items
where I can now have a set of instructions that's maybe a paragraph long versus
a page long that I'm giving these AI agents, and easier to tweak, easier to
maintain, easier to
maintain. And so I think that's really important. And so I think the other
thing that's important to me is that I'm very interested in this.
And I think that's why I'm going to be able to talk to you about the technology
I know based on what we just saw and I wanted to explain that the technology we
're leveraging and customer platforms supports multiple languages.
When it comes to voice right now voice is only available in English, but we
plan to expand that in the future with our roadmap.
So I'm going to make sure I address that question.
And can I just jump in there for a second? Yeah, it can auto do translations as
well. So even if you have your content in English, it does language detection
and can auto translate the responses into the native language.
And I'm just going to take a step even further, utilizing the customer platform
There's language translations for your agents there as well, utilizing AI. So
all of this together as Caroline showed that that platform slide really brings
the AI and customer experience and the agent experience that human in the loop
together.
Yeah, I've had real time chat experiences with people who speak German. I don't
speak a lick of German. And it's all through AI right there in the platform,
basically in real time allowing me to converse with these people across a
language barrier.
It's really amazing.
And Aaron, there was a question about how long it took to configure what we
just what you just demoed with the AI voice agent.
That's a great question. It can take obviously if you're if you're going for a
demo that you can take a few shortcuts here and there to get it to demonstrate
exactly what you want, but I would say that setting up something like that.
For all the edge cases you want is not going to take a long time. You're going
to start with the basics of what you want your AI agents to do and give them
responsibilities. And once you have that basic, basic foundation in place,
which really, even with testing isn't going to take more than, I don't know, an
hour and
a half for most people, if that maybe I'm saying too long. Really the what it's
going to come down to after that is watching and tweaking the language that you
use to tell the agents what to do tweaking it based on what you're seeing them
say tweaking based on the
ability that you're getting to make sure that they're behaving the way you want
, just like any agent, you can go in and you can manage them and give them, you
know, new tools to use.
And so, I think, yeah, it is hard to give a full answer to that because I think
it's a constant evolution.
And I think what's exciting to bring Paul back into this with the last slide
that he showed was the difference between AI chatbots and agents is that what
was before had to really be programmed and thought out and had needed more
upfront structure.
And here we're talking about generative AI that allows that has reasoning
skills and is able to make decisions right if you give it the right amount.
And then you give it access to the right data and the right tool set. And then
you watch it over time and optimize it over time it's definitely, you know, it
's, it's a big change, even within what we've been doing in the past year, which
is why everyone's talking about it.
But I'll go back to you, Paul.
And I also will say just to answer the question formally. I think it took me
about 20 minutes to set up that demo. So,
these are unbelievable questions and I appreciate you bringing this in. And I
think these questions that are coming in are really, you know, trying to, to
peel back the onion on.
How do you best use these AI agents? And we've all become very familiar with it
. So, if we could go to the next slide, Caroline, I think maybe we could just
continue the conversation about it.
And, you know, and, you know, there's a lot of different thoughts in the
marketplace from kind of a one giant, AI agent to do everything.
And you set the instructions and they're operating cadence or having multi-AI
agent teams. And I think, you know, we talked about that, you know, on our
previous slides.
But, you know, it really is the ability to handle and organize complex workflow
actions.
You know, assign work to this specific agent. So, in our world, when you create
an AI agent team, an AI agent team generates a supervisor.
And that supervisor is, I use that analogy earlier. It's really that greeter.
Is that person that's going to help me or that AI agent?
I think about them as people. I don't know. Maybe it's just me. But that AI
agent that's going to start me and understand what is my question and route me
specifically to that specialist, that person who can do things, that person
that can update data,
that person that can retrieve data from the system. And that's the real power
of it, understanding what to do.
And if you think about, let's say, a return process, the customer might come in
and say, "Hey, can you send me the details of my last order?"
I don't need an order number. I don't need an item. I don't need anything. The
AI can reason, based upon the dates of the orders that that customer has and
present them with the right information.
"Hey, I'd like to return a hoodie I purchased." Wow. Maybe I have 20 orders on
my timeline. Order number seven is a hoodie.
Once again, the AI is intelligent to understand what I'm asking.
Car set information appropriately, and then understand your return policy or
whatever policies you have. Hey, you've purchased that outside of the 30-day
window. Maybe it's a 30-day return policy that your organization has.
Maybe then it needs to bring the human in the loop, but really, assign and
specialize agent. You know, execute, refine tasks based upon all the tools you
have.
And as Caroline went through the different components of the customer platform,
from apps to data to the channels, maybe there's different ways.
I want to interact through WhatsApp versus through SMS versus through email
versus through phone. Maybe when I'm presenting order details in a phone
conversation, I want it to be short and concise.
When I want to just present order details in an email, it's okay if it's a
little bit more verbose, but you can train and instruct your agents on how to
do those things.
And that's really one of the powers here of the AI agent. And then, you know, I
think the ability to collaborate and move seamlessly through from one agent to
another.
Hey, I have a question about a return. One of my items was damaged. Where is my
order?
Hey, where is my prescription? Can you help me with that? Whatever it might be
to seamlessly transition those conversations from one special AI specialist, AI
agent to another.
And I think that's really, you know, one of the powers that we're bringing to
the table is part of our AI agent strategy and there's a lot of thought that's
gone into.
What is the best way to do this? Are there anything to add there?
Gosh, no, I mean, I think you're killing it.
I didn't need to put you on the spot, Aaron. Oh, no, I didn't have anything
prepared. I know I think I think you've covered it very well.
We do have a question that I was about the type and answer to that I think is
related in terms of like people really understanding their agents that can be
customer facing, but also maybe you guys can talk about the agents that aren't
necessarily customer facing.
You kind of do more of the task and the back end. You know, as we talk about
these workflows, there was a question for Michael about would this AI also fill
out information to help representatives, you know, find certain data that they
need like you're talking to your system or CRM.
Absolutely. And, you know, if you think about the customer platform, you know,
the standard, the ability to create objects in the system, the ability to
update objects and attributes in the system, the ability, of course, to read
those or get those pieces of information.
We haven't built in to delete yet. That's something you need to do on your own.
So, you know, I think if you think about that crud acronym of create read
update delete, we have the crew, CRU update. We have the CRU acronym that we
have out there, but all that's available directly through the
AI agent and the tools that you define for that AI agent to be able to leverage
. And there's also this idea of observability and, and being able to see what
the agents, how their minds are working essentially on the back end.
And we do have built in tools also run by AI that will go through an agent's
response and grade them on on how appropriate their response was and you can,
and you can see how well the system thinks it was able to answer any given
question or respond to an inquiry.
Yeah, I suggest that that could be a whole webinar in and of itself.
Yeah. And all of that information is available in reporting, including the
number of communications that are happening, the number of responses and how
they're stored, a scored within the system, and that can allow you to really
fine tune is necessary, the different
AI agent experiences should want to pop to the next slide, Caroline. Yeah, let
's do it. That's great. You know, and I think we, you know, as we talked about
and there's been a lot of questions about what are we thinking about from an AI
agent perspective and you know, is there a delivery expert?
Hey, where is my order damage product expert return expert, but always, always,
I think having the ability to escalate this and you know, I think we've read
about these things.
You know, these companies or the CEOs are like, I'm firing my whole CX staff,
we're going to do everything through AI.
And I think at the end of the day, you know, if you click to the next slide
there, Caroline, I think, you know, we talked about a statistic of, you know,
companies really CX leaders really believe that there needs to be a human, you
know, the human in the loop capability.
And 79% of CX leaders think that that is still an important factor in what's
happening in the CX space, right? And, you know, there's going to be those
situations where hopefully we can deflect, and you can deflect based upon, you
know, your use cases, 30, 40, 50, maybe even more percentage of those kind of
inbound inquiries, but always given the ability, no matter what the channel is
to escalate it if necessary to be able to take care of things.
Yeah, and we're actually a few slides down, we're going to be able to show this
live, so I'm excited about that.
But before we do, you want to go to the next slide.
Awesome.
So, you know, this is the acronym that I was talking about before, smart, and
whenever I think about our AI agents and our AI agent teams, right, and AI
agent is one component of an AI agent team that you have.
And if you think about your contact center, that's a team of individuals that
helps you interact with your customers.
And I think, you know, when we think about the AI team, once again, specialized
, what is their skill set?
Let me route the conversations to that skill, right, and customer has, you know
, Q-based routing, skills-based routing.
Similar here, when I'm thinking about AI agents, how do I get the right
conversation to the right AI agent to be able to respond to correctly?
And now this one here, multi-channel, I can build one AI agent to respond
across all the channels.
I don't need to have one for SMS, one for email, one for voice, one for chat,
one for WhatsApp.
I build one AI agent, and I give that AI agent the appropriate instructions
that I want to have it handle.
And, you know, it's not one tool for this, one tool for that.
Advanced reasoning, and the keyword here is reasoning. And if we think about
that AI chat bot I talked about before, there's no reasoning in there.
I'm just driving someone down a path, and maybe I define intense. I don't have
to do that anymore.
It's all about the AI understanding and reasoning. What is someone asking about
Responsive. You know, once again, handle complex situations. If that's creating
data, if it's updating data, those are things that weren't able to be done in
the past.
And then this last one is teamwork. And I think about Caroline, myself, and
Aaron here on how we're transitioning this conversation back and forth between
ourselves.
How do these AI agents transition complex queries from one AI agent to another
AI agent to make that customer experience the best that it possibly can be?
Go to the demo.
Yeah.
I'll take it from here, and let's carry on, you had on the other thoughts on
that.
No, no, I'm eager to get you started on the demo, actually.
Great. Yeah, so we've talked about our smart agents, and something that I want
to demonstrate here in addition to human in the loop, which is the main purpose
of this demonstration, is that, again, we are multi channel with these.
So this is an agent, the same agent that was responding to me on the phone. I
can, well, sorry, I should say team of agents responding to me on the phone is
the same agent, a team of agents that's going to be responding here in a chat
conversation.
And what we're going to see here is a an agent responding to a chat inquiry,
and they're going to use the internal knowledge base, the help center from this
organization that the agent works for.
They're going to be using the knowledge base to answer a customer's questions.
And then when they're asked a question that they don't know the answer to, they
're going to loop in a human agent for more support.
So let's take a look at this and I'll try to narrate as we go. We have a
customer who's made a car rental reservation and they're reaching out about
additional services offered and the AI is responding using the knowledge base
to answer the question that was asked.
Now here the customer is responding with an additional question that the AI
does not know the answer to, and we can see here that it's routing to a human
agent who once assigned takes a minute to look up the information.
And then once they have that information, they can give a full response and
maybe options to add something to the reservation and can take it from there.
And so that is the power of human in the loop we're not just relying on these
agents we have people who can step in to make sure that things are going well
to, to, to, I don't know, give a thumbs up on a, on a, on a return, or, or
check information that isn't otherwise available to the AI.
So thanks for playing that second demo, Caroline.
Yeah, that was a great demo and maybe we revisit that as well if people want to
see that again after we get through all the content but.
Yeah, I think that that.
It's an interesting example of like something outside of a normal question
right where the human needs to get involved so around a car seat if you rent a
car right and you want to know like.
Specific details of a car seat, and that's typically something you need to talk
to a human if everyone's I've been there as a parent when you rent a car you're
like you want to know like what type of car seat is again, you know, be toddler
booster or.
You know, so that was the example we came up with in terms of like wanting to
speak to someone to be reassured in terms of what you're getting and reserving.
I think now we can go to Q and A if you guys are ready.
Yeah, let's do it.
So we've had some question we have a question around that I want to make sure
that we address around a voice and HIPAA compliance.
Okay, I can jump in there so our.
A voice is only available using customer voice today and I think is Caroline
mentioned right now it's only available in English.
Our agents are and we use kind of we don't use the LLM that's available to
everybody we use our own private LLM it is an open chat GPT but it's specific
to us that data is in shared outside of your particular environment.
It's not shared with anybody else your knowledge content your data your
anything is only yours so open AI and the model we do use is HIPAA compliant
and we can sign a BAA associated to that.
But from a voice perspective it's only available customer voice today.
Thank you. It can maybe you know for everyone's to make sure we're all on the
same page because this the space of movies so fast can you talk about like LLM
's sort of clarify.
Yes, no problem so large language models and there's quite a few out there and
probably the one that a lot of us have heard about is open AI and open AI is a
company that has to designed an LLM that's called chat GPT.
And we are leveraging a LLM which is chat GPT 4.40 mini is the LLM that we're
leveraging for our responses our generative our content or anything that's
happening within the platform.
Good to help Carolyn. It does thank you. Awesome. And then there was a question
around sort of that bi directional human in the loop so talking through more
about we didn't show it today but how it can go from AI agent to human back to
AI agent and the quick answer is yes,
it can do that I don't know Aaron or Paul if you want to elaborate in terms of
like a use case or how it would work within customer.
Yeah, absolutely so I my demo was very quick but if it were to continue going
you might hit a point in that interaction with the the rental company where the
human agent no longer needs to be directly involved and would hand the
conversation back off to the AI agent
who could continue answering questions or accessing tools to help the customer
in other ways as it was given the resources to do.
And I imagine in terms of when we talk there are a lot of questions around
configuration that that's something that you do in the instructions.
Can we talk about like how that like is set up a bit in customer.
Gosh yeah instructions are sort of the heart and soul of an AI agent and a team
of AI agents.
When I'm setting up these demos I'm talking to my agents and I kind of touched
on this before I'm talking to my agents like I would talk to any real human.
Employee on my team. I'm saying hey this is what you do you work at a car
rental agency your job is to greet people and be professional and ask them
questions about why they're reaching out if you don't know why they're reaching
out dig in a little bit if they're
in queries vague ask questions that will give them get them to give you more
details and that's a pretty common thing that we all need our agents to do in
any sort of customer facing environment.
But then you can get more specific you can say if they ask you a question about
car rentals I'd like you to go to the knowledge base and find the relevant
information and give it back to them in an easy to understand way.
And again these are I could take what I'm saying now and put that almost verbat
im into the instructions or a agent and it would understand what I'm saying and
it would it would follow those directions.
Yeah I think an extension to that is Samir came in early on we didn't talk
about like healthcare use cases and so he said for a company you know providing
healthcare.
How does an AI agent stay have a compliant and not accessing patient data
unnecessarily. So Paul I know we have things like guard rails or we have things
later very like because these are so specialized the specific instructions can
you talk about like how you would set up to make sure
the agent doesn't really capture the wrong piece of data. Yeah well once again
we're using a private model within open AI we're not using the public model.
And that private model is specific to your account your your the information
that you're using with our agents and how it's generating it and how that
content is being returned is only for your particular account.
And that's not being shared across anything. The other thing there is you know
you have the ability to define what data and what components you want every AI
agent to have access to.
And if you get to that point where you feel like maybe it needs to be
transitioned and that's the power of this AI you know human in the loop
capabilities.
And we're not going to be able to explain those instructions hey we've given
this information they've asked another set of questions that we're not
comfortable passing through.
We're going to then route that to a human to be able to respond to so those are
all the sets of instructions that you can give to your.
And the things that we use is rag within the system right and it really is to
really stop and make sure those answers are you know we're not hallucinating.
We're giving the best responses as humanly possible and as Aaron talked about
we're scoring those responses and we score those from ABC E.
Or F but we score those and we only send out and we will only let the system
send out A, B or C scores that are out there so that we're feeling very
confident and we will continue to try that.
And it fails that's where we're going to go and say hey we need to route this
to a human but always having that human capability to execute if necessary.
Great and I'm also thinking like in healthcare the different customers we work
with, you know it might be around that front desk experience just since people
get more comfortable with it you know and scheduling appointments.
You know things that don't necessarily require a lot of information it's more
around like making that.
First appointment scheduling or seeing availability or reminders right in terms
of like a use case that might not get too deep into PII.
Awesome.
I'm just going through some of the questions.
There are some questions around maybe with AI agents like the stats that are
available, like some of the things that
you know our system shows in terms of like the I guess productivity of AI
agents.
Neither of you speak to that.
So we do have native AI agent reporting available within the platform we're
going to continue to expand that as we continue expand the usage of the system
but it does show me all the conversations that the agent.
All of you know how many of those messages had different scores associated to
those so we're capturing all of that information within the platform.
So you know as we continue to move forward we're going to continue to expand
similar to all of the other types of data points that we have within customer
to allow you to do those things.
You know one of the other things that I think about in a lot of cases is
individuals you know sometimes come into systems unauthenticated right and we'd
love to say that everybody comes through that authenticated chat and I think as
you saw as Aaron went through his demonstration.
You know we're very security conscious about sharing data and that's a massive
topic but even through unauthenticated chat we could prompt someone for their
email address or some other unique identifier.
And from there if we didn't have an authenticated chat experience we would
prompt that person for that six digit verification code and similar that you
saw Aaron do there.
And you know in the demo and we've done you know if you do online banking or
you do anything now I tried to log into one of my investment accounts and hold
on.
I know you've logged in from this computer 50 times but we're still going to
send you a six digit code to make sure that you are you and you're on your
device and you have connection and we're doing that with the chat and we would
be sending that either to SMS or email so they're not.
It's not coming through the chat if they were trying to spoof something so you
know we've taken a lot of precautions in that but you know this is a big area.
You can always have authenticated individuals but we consider if you have that
six digit authentication verification code that you authenticated you can do
things that are there.
Anything to add their Aaron.
Yeah, something that I thought was really neat is that if you are on something
like an unverified chat that comes in and you're not recognized by the system
right away say you you get routed to like a new brand new customer timeline.
And it says hey do you want me to send you an email and you say yes and me an
email with that verification.
It might start to be confused at first it's going to say oh I actually don't
have an email on file what's your email address.
And at first I thought I was getting away with something because I was like oh
I'll just I'll just put in my email and like I can get this information but no
it will then find the profile that belongs to that email address and then once
you get that verification code assuming that you own that email address you can go get it it
will move you over to the right place and it knows who you are anyway, which I
just think is a really nice touch.
Yeah, and I just saw response in here and Jose I think we can, you know, spend
a little bit of time as necessary in the future to understand your specific use
case and understand that a little bit more we're very confident and how our
models respond but
you know everybody is it could be a little bit more specific so I just wanted
to make sure that I got to your question.
Yeah, that's great. Thank you.
There are also some questions I can I can take the answer about pricing for
this.
So two weeks ago when we made our big announcement about AI being native to our
platform we also talked about
conversation based pricing so what that means is that that's already on our
website if you go to customer.com and look on the pricing tab it'll show you
that
we are we've adjusted our pricing model to charge based on the number of
support conversations you're having we're not like we said AI is not an add on
so we're not charging
based on, you know, seats don't make sense with AI agents but you know the AI
is is built into the pricing which is based on the number of conversations you
're having.
So we, you know, we spend a lot of time doing market research to validate and
work with our customers to validate this way of pricing.
And so that's that's on our website today.
And so I wanted to direct people there and I'll add in the link but just to
address some of the pricing questions I wanted to jump in there. Paul and Aaron
There's also a question around like passing between AI agents and humans and
across channel.
So I don't know if there's anything that you can talk to about I think the demo
showed it we can almost show it again around sort of that seamless experience
for the customer right going between AI agent to human
and I think, Aaron, you might have even shown it across the different channels,
but correct me if I'm wrong.
Sorry, I was answering a question in the chat. What was the question? Oh, sorry
. No, I'll take it.
Okay.
Thank you.
Oh my God, I just forgot what you asked. Go ahead.
Well, I think we've thrown a lot of things at our audience today, right? We've
talked about like on the channel like all the different channels you can
service and like, even before AI agents I think just a little bit more.
So by agents, I think just a level set with the audience and understanding
customer.
There was this ability to have one support conversation that could span
multiple channels that we are really excited about, right? The humans would
take human could pick up the phone customer voice, which is native.
So I'm going to clarify that based on some of the questions. We launched
customer voice this fall. So it's native to customer. It's a channel and
customer.
So an agent could pick up an answer on the phone, but then if you need
verification or you want them to send a screenshot of a damaged product, you
can then go to SMS in our system.
So that seamless transfer between channels based on what the customer needs at
the time, I think is amazing.
And now we've added another thing to that to say, Hey, AI agents can do this as
well.
So I think some of the questions were around like going between channels, going
between agents and more clarity and like exactly, you know, how that works.
And Carolyn, I think that that's the power of the customer platform, right? You
don't have to file another ticket to go on another channel to go, right?
I think about multi channel versus omni channel. Yeah. And the term omni
channel, really, and it's a very unique component of the customer platform,
where, you know, if you look at, and I could go into this for hours, but if you
look at our data model,
we break every message out independently in our data model. So it's not just
this big blob of information inside of a conversation or a ticket.
Every message is broken out. The first message could be SMS. The second message
could be chat. The third message could be email. And that can be in voice.
You could start with a voice call, move it to a SMS, transition it to a chat,
move it to an email. However, you want all within the same conversation. So it
's how you think about how you communicate with anybody.
And those AI agents have the ability to seamlessly move that. And you saw Aaron
go from a voice call to getting sent out an SMS to, Hey, let me send you that
content via an SMS or a tax store and email directly.
So a lot of power there can move these conversations from one channel to
another is necessary.
Yeah, thank you.
I think we have a few more minutes and so many questions. I feel like this is
the beginning of a series that we can do on webinars.
I'm on AI agents. Because today we just touched about the use cases and how
they could be used and applied to customer service. But certainly there's a
whole series that we could talk about like how you actually build and deploy
them and test them in customer, which this wasn't necessarily that webinar but
I love these questions.
Aaron, as you were going through the questions, is there anything we didn't
address live that maybe we could. And the next few minutes.
You're talking to me on the spot again. Oh, yeah, I'm on the spot to trying to
find it.
Oh, no, no.
Well, here's one that just came in. How are agents able to access external API
's.
And that's, that's a bit of a complicated question, but the short answer is
that we build out tools and you can build out tools and give them to your AI
agents to access all sorts of things right now that's mostly focused on
internal systems.
But there are going to be tools that allow you to access third party systems as
well and you will be able to set those up and access, not only access
information, but also potentially action item on things outside of the system.
So for anyone who understands API's sending put requests post requests things
like that.
Yeah, and I think the power also, Aaron is, you know, that might not be
available as a tool today, but the power of the customer platform allows you to
interact with workflows that can make those API calls to get additional data.
So, Bob, you I could make a retrieval of additional customer data.
If necessary, use that as part of the AI agent experience.
I can do a put request or a post request out to a back end system. And if I'm
talking very technical I'm sorry everybody that has no idea what I'm talking
about. But how can we talk between multiple systems.
We have our workflows. We have our AI agent experience. And all of it really is
the goodness as I said our CEO is you were there. The goodness of the entire
platform coming together.
Thank you. And I know we've only touched on the expertise you both bring to
customer in terms of AI agents. I think these questions are so awesome. I so
much goodness.
I would recommend that we continue that that if you have more questions, please
, you know, contact us get in touch.
You will get into a meeting where you have access to go into your use case with
Aaron or Paul here. And so we definitely encourage that and stay tuned. We have
more webinars to come. I mean, a lot of the questions will give us ideas your
feedback will give us ideas on other
webinars that we can produce, you know, to continue this topic, this discussion
. So I really am thankful for everyone's participation. Thank you, Paul. Thank
you, Aaron, for coming on and sharing such great expertise. Thanks to our
audience who have been so active and in posting questions answering polls.
This has been fabulous. And if you're a customer, you have access to our
customer community. So we encourage everyone to post questions and start a
dialogue there because this space is moving so fast, you know, my own personal
experience of talking to our customers is there
learning as they deploy and test AI agents. And so, you know, if you're a
customer, you have access to that community. So please take advantage of that.
And so we're going to be bringing more webinars to you. So please, you know,
stay tuned to hear about what webinars will bring back fill out the survey if
you can. We'd love to get your feedback and, you know, thanks so much everyone
for joining us today and we're going to conclude the event.
Thank you.
Thanks so much, everyone.