Hey, guys.
Welcome back.
So we are now going to look at vertex AI use cases for a LM and generative AI, and we are going to
look at contact center as the use case for now.
So generative AI, large language models are used for opening up new opportunities across the board.
We can make use of complex data and access it in a variety of ways, which was earlier considered impossible.
This can now power online interactions customer scenario.
It can also be used to generate more content and unlock infinite possibilities of data for enterprises.
So Google is opening generative AI.
So Google is opening generative AI across the LM and a portfolio to benefit AI practitioners, a developer
or a business user, you will benefit from this innovation.
So if you are imagining I across the.
Different stack it, as you can see from this in the vertex model.
So in the model garden, you will have access to the latest Google research and brain have published
in future.
Google is working on expanding this to other open source model.
Google is now introducing generative AI APIs which will work on the top of specific model use cases
so users can use Palm API to do clustering and gender and generate summaries.
You can also do generative content using generative AI studio.
As a developer, you can use generative app builder to actually create specific applications for specific
contexts.
For example, you can use info bots to just point to a document base and generate a conversational experience
on top of it.
So Google packages all this technologies into a specific industry like contact center, which is known
as CCI, as you can see.
Then the next one is a document, AI and discovery, AI and the health care AI so which makes it easy
for all the end users to consume all the technology from this innovation.
So Contact Center AI has been around for five years, which has given Google deep insights into challenges
faced by both customers, agents and contact center agents.
On the user side, there is a long list of frustration of long wait times of being down hierarchical
trees and not being able to get into the info they need for the task.
They want to be resolved in an intuitive manner.
On the agent side, there is a constant churn and higher onboarding costs associated with this contact.
Center managers are frustrated as they feel they lack the contact center.
They feel they lack insights and treat contact centers as a black box.
So Google CCI is supercharging conversational AI contact Center has a vast portfolio of products built
on top of CCI.
So virtual agent development platform powered by Dialogflow, where you can create conversational AI
experience to automate tasks, help users resolve issues without even reaching out to live agents with
agent assist you when the conversation gets escalated to a live agent, Google can assist with agents
and make them empowered to handle questions appropriately.
With contact center AI insights, we can look into the entire conversation and help generate actionable
insights for your business decisions.
So all of this is enabled through Contact Center AI platform, which was launched last year.
So Google Lens in CCI, the way you can generate AI used in CCI is through three issues.
So one is user first experience, which all the users with the platform, the next is focused on developer
friendly, generate a high level quality generative AI and we can calibrate about being.
We can provide a platform of the response being controlled so you can control what responses and sources
you want.
The responses to come from.
Here is an example of CCI platform which Google has implemented and you can also implement this to using
the info bot and other solutions.
So this talks about some content done through that.
So we are walking through some use cases like how you can use it.
You can just point it to a domain and it will have access to the flow.
And on top of it, the developers can also source the content where you want it coming from.
So if you don't like the if you don't want it from the outside world, you can explicitly list the data
sources.
So you want this coming from into your.
So here you are specifying the content of your website, other websites, and the general knowledge
of Google I.
So that's the flow.
It looks for your local content.
Then the content you have specified.
If it's not there, then it uses the bot knowledge to try to get the solution.
So prebuilt flows.
Google has looked across industries and built a variety of use cases.
You can add to your user flow with a single click.
Examples of this can be authenticating users checking order status and explaining and explaining a bill
and click.
If you add your dialog flow and you are provided with instructions on how to set up your API to handle
that, the next one is how to build a.
How you build graphs in graphical interface.
You no longer need to specify every possible route which is handled by AI.
You just need to specify the business logic and the task your bot should be able to complete here.
So there is also the third way of doing it.
If you don't like the way of doing graphs, you can use natural language instructions and you can choose
the type of flow you want to use here.
And the next one is agent assist.
So a few features which live agents and custom live agents and help to serve customers better.
So before call summarization, give them the context of the conversations that went into the bot beforehand
and after summarization helps them to give a starting point to do a call wrap up.
Most of the time they don't even need to do anything.
The data is accurate.
So if you look at this one, the data that's provided is accurate and we don't have to do anything here.
So agent Assist is the next one that will be coming up And.
In the agent assist.
It uses an info bot tailored for live agents has to do is to point to the set of a set of data sources
and you can also see a live agent as quotient to the bot.
And bots are powered by the same tech that it first look for the local tech local content.
If it's not available, then it looks for global content.
This enables a live agents to do deep linking and for developers it's super easy to set up in their
agent as conversation profile and all they have to do is select the features.
The last one is CCI Insights.
All the conversational data from human agents bots can easily together use for analysis and customer
easily can be used for analysis.
Whatever people are calling what's top of the mind and data would be available here.
And last one is customer inquiries where all the questions coming, the top trending topics are available
and that that can be used to make business decisions later on.
So that's all I wanted to cover.
Thank you for joining.