Okay, we'll bring this home by making a quick flow of agents to solve a little business problem.
Why not just a toy?
Example.
Let's start by going to knowledge Bases and add another document.
Let's create a new text thing and let's let's call it a stock.
It's going to be what the shop has in stock.
And what we're going to have in stock is going to be a few Apple products.
There you go.
An Apple Watch Series 11, iPhone 13 Pro Max and MacBook Pro.
Oh, we might as well make it an M4.
There we go.
That's going to be the stock.
And we'll create that as another knowledge base.
Of course it could be something much longer.
There we have it.
Now we're going to set up a little, uh, agent workflow okay.
So we're going to try out the workflow functionality right here.
And we are going to start by picking a template.
Why not to get us up and running.
We'll pick the qualification flow template we looked at earlier as our starting point for our little
experiment.
And let's just go through and edit this.
So the first agent is called the qualification agent.
We're going to change this to being the main agent, the one to kick off the conversation and we're
going to keep it very simple.
The conversation goal, which is the prompt, we'll say you're a customer support rep at a store that
sells Apple products.
You direct the user's question as appropriate.
I'm turning on override prompt, which means this completely replaces the prompts that we put in the
agent tab there.
Who will we have?
Let's let's pick Miz Walker as the person that will answer the phone.
Miss Walker will take it.
And, uh, that is a good setting.
Um, and we will, uh, we will make sure that she does not inherit the knowledge base.
So she is coming in with no knowledge coming in to take this call.
Okay, that is the first agent.
All right.
Now we're coming to technical support.
So for technical support, we are going to say that the prompt here should be you're able to answer
general questions about Apple products.
And we will say that should override the previous prompt.
We will have this being someone let's choose someone new.
The Russell outgoing and excited.
You can be our our Apple products person.
You need a knowledge base for that.
Don't inherit.
Instead, we're going to give you a document.
It will be the Apple product details document.
There.
There we are.
Nice.
You've got the knowledge.
You've got your prompt.
It overrides.
We're set with technical support.
We're going to change the name to be product support though.
Make it a bit more accurate.
Product support is done okay.
And now to billing support we're going to change this to be stock spec.
There we go.
Uh, and this is going to be someone that can answer questions about what the store has in stock.
So let's put exactly that.
Let's override the previous prompt.
Who should we have for this one.
Have someone let's have Stokes.
Don't know what Stokes sounds like.
Uh, and we need to give them a knowledge base.
We won't inherit the knowledge base.
We'll add a document.
We will add stock in there.
There we go.
We have stock specialists.
One thing we've got left to do, we need to set these edges.
These are the conditions that decide whether the main agent routes this way or that way.
Let's set that now.
Okay.
So I'm going to select this edge.
It's called it's an LM condition.
The label is technical issue.
Let's change that to be product question.
The user has a question a general question.
About Apple products.
There we go.
That's done over here to this other edge.
It's a LM condition.
It's a label is billing issue.
Let's make that stock question.
And let's say the user has a question about what Apple products the store has in stock.
That seems crystal clear to me, which is always a good sign.
I think we are ready to give this thing a try.
Okay, let's give it a whirl.
Press preview and then call AI agent.
Hello.
How can I help you today?
Hello.
How are you?
I'm doing well.
Thank you for asking.
How can I assist you with Apple products today?
Yeah, I'm interested in what the latest model of the Apple Watch is.
The latest model, the Apple Watch, is the Apple Watch Series 11.
There's also the Apple Watch S3, which is a more affordable option, and the Apple Watch Ultra three,
which is designed for ruggedness and endurance.
Do any of those sound like what you're looking for?
Yeah, they all sound great.
Thank you.
And that.
Finished it.
It terminated.
How was your conversation?
Very good.
So let's try it again.
Let's ask it go a different route this time.
Let's see what happens.
Hello.
How can I help you today?
Hey, how are you doing?
I'm doing well.
Thank you for asking.
How can I assist you with Apple products today?
Yeah, I'm wondering what models of the MacBook Pro you have in stock.
We currently have the MacBook Pro M4 in stock, and there you have it.
That's, uh, that is a successful test run.
So you just saw a pretty simple example of being able to ask a question.
And based on that, it was being routed.
And you notice it's not as if you have to repeat the question or something.
It's that that whole question was being routed to the right rep.
And of course, what you'd find is you can imagine from this very simplistic example and picture, is
that if you then asked the specialist a question about the product, they wouldn't be able to answer
it.
You'd have to add in more edges to allow for the conversation to go back.
Um, but this is now we're not going to go into depth of this tool because we're going to be hooking
up our voice agents to Nw10.
But I wanted to show it to you, and I wanted to say that if you have simple use cases like this, if
you just want to build something, which is a customer support rep with a knowledge base and with some
ability to move between different, different messages, perhaps different types of operator.
Then you have that tool at your disposal.
11 labs can do it all, and it's really easy to use and it's really high quality.
So experiment with it a bit and I hope you enjoy it.
And that's a wrap on our first day of experimenting with 11 labs and building voice agents.
I hope you were blown away by how easy it was to build a bunch of different voice agents, and to throw
in knowledge bases and a bit of a workflow there as well.
Uh, we, we got we got a bit into it.
As I say, we're not going to go too much more because we're going to be using innate and still as the
kind of back end to what we build with voice agents.
It's the marriage between 11 labs and nine that is so very powerful.
That's what we're going to be doing, and we're going to be starting that tomorrow.
And I can't wait to get there.
But as usual, first we have to take a moment to say, wow, 40% of the way through.
I hope you're starting to feel a bit more of a pro.
You certainly will after tomorrow when we hook these two platforms together.