SPEAKER: Today, we're going to show you
how Google's Generative AI App Builder, or Gen App Builder,
can save you and your development teams
time building an enterprise-grade customer
experience.
Gen App Builder gets you going by completely removing
the boilerplate for use cases we call Gen Apps,
such as bots, chat apps, digital assistants, custom search
engines, and more.
Gen App Builder starts by learning your data,
so it's customized from the start.
All of these previously took weeks or months
for a development team to set up.
Now you can get a deployable bot within minutes and more time
to focus on what makes your app special, not the boring setup
code.
Let's walk through how I, a developer at Cymbal Bikes,
can set up my very own chat ordering experience
through the Gen App Builder.
Let's get started.
We start by adding a URL.
Now it's time to load a few company-specific data.
We have several important documents in internal sources,
like PDFs, CSVs, and more.
It's important our app understands
our product catalog, policies, employee guides, and FAQs.
Accepting and indexing our info as it is
saves us data prep time since we don't
need to extract and structure our data.
The data is stored in the company's
private protected environment, and Google will only use it
with the company's permission.
This is achieved through the same identity and access
management your admins are using for the rest of Google
Cloud for fine-grained control.
Now let's really get going.
I can pick either a search or conversational chat.
For a fully seamless experience, pick both with just a click.
Let's go through the chat creation experience today.
My bot will try to respond with the knowledge found
in my content sources first, for example, answering the store's
return policy from our FAQ.
If the knowledge base doesn't cover your user's question,
we can define what we call generated
responses, which leverage the foundation model's
generative capabilities across multimodal and multimedia
responses.
I can use this interface to define
granular control in my app, much easier
than setting up these rules in my code.
Here, for example, I can choose what types of responses
to allow or even set specific terms I do not want to appear.
I can also disable generated responses at any time,
and my bot can still answer complex questions thanks
to Google Search technology.
In this use case, let's keep it on.
A comprehensive bot doesn't just provide information.
It can function as its own application
by completing transactions and other user-guided tasks.
A robust app will have user workflows.
For getting ahead on common use cases,
like Check order status or Explain bill,
pop these prebuilt flows into this graph-based interface.
I can also use this for my own custom workflows, as well,
or leverage a prompt-based flow, where I can just
specify the logic using natural language instructions,
great for collaborating with product management.
AI dynamically handles all the potential paths.
AI is not only helping the customer,
but us to build this out.
These simple instructions here help
understand the user's intent without having to hard code
a rigid control flow.
Now as we're getting closer to deploying, here,
we can use out-of-the-box integrations that make it easy
for me to launch my bot to my website and popular messaging
apps.
I can also connect with telephony partners.
Let's first take care of integrating this bot
into our existing website.
Once we're ready to go, the Gen App Builder
creates the chat widget code for me.
I can share this with our front-end team
to quickly integrate into the website.
Our multiturn, multimodal bot is ready to go.