Salesforce, Inc. (CRM) Earnings Call Transcript & Summary

Hello, everybody. Welcome to the Service Cloud Spring '25 release highlights webinar. We are really excited to be here today. A lot of our customers have been asking us for information on our product releases. And today, we're going to be sharing all of the latest innovations that are going to be coming to market in February. My name is Rebecca Curtin. I look after product marketing for Service Cloud across the APAC region. And I'm joined by 3 of our product experts, who have really, really worked closely to help bring these products to market. So you're going to hear and see things from them firsthand. So we've got Harish and Kevin, who work in our Service Cloud product management team, and we've got Will, who is our Field Service specialist, and we'll be taking you through some of the latest innovations for Field Service. We would like to begin by acknowledging the traditional owners of the land on which we meet today and recognize their continuing connection to land, waters and culture. We pay our respects to elders past, present and emerging. A bit of housekeeping. You will be on mute today throughout this webinar. If you have any comments or questions, please put them in the Q&A box, and we will answer your questions throughout the webinar. We will come back to them during the Q&A. And if we haven't got time for everything, we will follow up afterwards. There's a lot of related content that we're going to be referring to throughout the webinar, so please feel free to download them. Hopefully, you'll find that information useful as well. We will definitely be making some forward-looking statements today as we're talking about our product road map. So please make your purchasing decisions based on the products and services that are available in your region, and thank you. We know you're super busy, and we're really excited to have you here on this product road map journey with us. Okay. So before we get started, I thought it would be interesting or useful just to give you a bit of an overview of our release marketing schedule. Salesforce, we release products 3 times a year, and they're typically tied to seasons. And these seasons are U.S. seasons. So if, like most of us here, you're not based in the U.S., that can be a little bit confusing. So we've decided to put all of the releases aligned to the months, which I actually found really, really helpful. So today, we're covering the Spring '25 release, which is going GA or is going to be generally available in February. We have another release in June, which is our Summer release, and then our Winter release is in October. And another thing to note is that about a month before each release, we have a release preview, which is where we provide detailed notes on all of the innovations that are coming to market. We make them available on our website, and there's just generally a lot of information that's quite detailed that can answer things such as what is the SKU that I need for this? How do I set up and configure this product or this feature? So we will provide links to those resources, but just to let you know that those are available. So because we're going to be diving quite deep into some of the innovations, I just thought I'd give you a little bit of an overview of the Service Cloud platform. We can't assume that everyone knows all of the products that we provide at Salesforce. So today, we're really going to be covering everything you see in the diagram. From the left-hand side, we're going to be talking a lot around self-service with Portals and Search, right through to our Service Console and some innovations there. That's part of our contact center, and then again through to field operations and our Field Service technicians. And when we say that Service Cloud is the most complete genetic platform for every kind of service in any industry on any channel, what we're really sort of referring to here is that from the -- again, on the diagram, your AI agents powered by Agentforce are going to be able to deal directly with your customers and support them and resolve issues with them directly. But if it gets to a situation where actually we need to involve a customer service rep, you can see me hand off that case information directly to a customer service rep, who can then pick up the case and deal with the customer directly. And they're going to have AI in the flow of work, which is going to help them be more efficient and provide a better level of service to the customer. And again, all of this, in terms of all of the Service Cloud functionality and all of the AI functionality, is available on 1 single Salesforce platform, and you have the added advantage of getting -- of being able to access additional data and insights through Data Cloud. So just wanted to give you that overview before we jump in. So what are we going to be covering today? I'll give you a quick whistle-stop tour, but then I'm going to hand over to our experts who are really going to bring it all to life with some fantastic demos. So first off, we've got -- within the Service Console, we've got Service Assistant. Now this really is a fantastic feature that uses AI to generate a service plan for your service rep so that they can actually provide much more tailored assistance to your customers. From -- we actually have a completely new offering called Employee Service, and what that's going to provide is a unified AI platform, which has got integrated with HR systems, third-party HR systems, which means that your HR team are going to be able to provide tailored employee information and support in one place. And also, your employees are going to have one place that they can go to, to get all of the informations that they need without having to switch between different systems. And then moving on to Field Service, we have data capture. This is really a fantastic feature that is really going to be able to pre-populate and pre-fill dynamic forms for your technicians so that they can actually get the job done faster. They are no longer going to have to manually fill in information whilst they're on site. And because the forms are dynamic, they can actually adapt so that the -- and react to the information that the system needs at that time. So again, the field technicians are going to be able to work more dynamically and more efficiently. And then moving over to, again, self-service. We have agent for scheduling for Field Service. This is really going to be a complete game-changer for our customers because it's going to give them the ability to schedule appointments directly on their own terms 24/7 so that they do not necessarily need to keep contacting you to be able to do that. So again, this is where we're going to be using an AI-powered appointment and scheduling system. And then moving over, last but not least, to real-time monitoring of agents within Omni Supervisor. This is going to give the supervisor the ability to view in a list both your AI agents and your customer service representatives and dive into some of the conversations that are being had and jump in and support where needed again. So just giving you some real-time insights as to what's happening across the contact center organization. So that's a whistle-stop tour. I'm now going to pass over to Kevin, who's going to bring all of this to life. Over to you, Kevin. Thank you.

Thank you, Rebecca. Hi, everyone. So good to be here with you all today. My name is Kevin Qi, I'm the Associate Product Manager here at Salesforce on our amazing Service Cloud teams, building great products for you all. So let's go ahead and waste no time and dive right into the very first innovation that we'll be bringing to market, and that is called Service Assistant. So as you heard Rebecca mention briefly, what is Service Assistant? As its name implies, it is your trusted AI assistant that really helps service teams close cases faster and more effectively. And it does this by generating a step-by-step plan for your human service reps to help address the case from the very start to the very finish. It's contextually grounded, really relevant and pulls in all the data around the case, the engagement history, the customer, and combines that with instructions on the back end that you'll see to inform the step-by-step plan. It's very powerful in not only helping your brand-new service reps, for example, who are still onboarding, to get the hang of the ropes, but also your more experienced representatives, who want to make sure that they're not missing a step or staying up with the latest compliance and guidelines. And so without me telling you, I'd love to show you. And so with that being said, let me take you into a demo. All right. So in this demo, I'm going to take you into a day in the life of Kanika. Now Kanika is a service rep at WhiskerWorks, which is a pet supplies company that specializes in custom products for all your everyday pets. And in today's day, Kanika opens her Service Console and sees that she gets a case from the customer, Jane Hammock, who's inquiring about a sizing issue with her custom cat tower that she recently ordered. Now before Service Assistant, Kanika would have to read through all the details of the case, extract key information and figure out what she needs to do to actually resolve this case. But now, thanks to Service Assistant, all that is handled for her. As you can see on the right-hand side of our screen, Kanika sees that Service Assistant has generated a service plan for her to tackle this case. Right away, she can see a high-level summary that gives Kanika what she needs to begin. She goes ahead and keys draft plan, and just like that, a detailed plan is generated for her, tailored to this case and how to resolve it. Kanika sees that the first step is to gather information. She needs to confirm the order ID, which is automatically extracted by Service Assistant, and also requests for some additional information from Jane, including things like product dimensions, photos and actual dimensions to verify that there was an indeed issue. So since Service Assistant is natively integrated across our Service Cloud platform, Kanika can act on this by using the Draft with Einstein functionality and selecting a pre-configured e-mail prompt template called Gather Information. In just a couple of seconds, we see that Einstein generates a thoughtful e-mail in the brand voice of WhiskerWorks and also requests for the additional information that Kanika needs from Jane. So Kanika reviews this e-mail. Everything looks great, and she goes ahead and hits send. Just like that, in a few clicks, Kanika can check off the first 2 steps of the plan, and she's already well on her way to resolving the issue. Now Kanika continues to work through the case, and she takes the information that Jane provides, crosschecks that internally with her product team and manufacturing team and discovers that indeed the manufacturing team made an error. No worries, Service Assistant informs Kanika that she needs to offer a replacement at no additional cost. Jane gladly accepts, and Kanika proceeds to go into the last step of the plan. Now WhiskerWorks has a company policy to always send a resolution e-mail to the customer, informing them of the summary of what had happened, what steps we're taking to resolve it and also offer any products that might go well with the product that the customer ordered as a cross-selling opportunity. So Kanika goes back into the same flow as before and uses the closed case template this time, gives it a couple of seconds, and we see that Einstein is able to generate a summary of the case, also provide the tracking details for the new tower that Jane will be receiving and recommends some complementary products, like a wall-mounted shelf or a customizable scratch pad that goes really well with the custom cat tower that Jane has just purchased. Kanika likes what she sees, so she goes ahead and hits send, checks off that final step in the plan and is able to close it out. And just like that, with Service Assistant guiding her along the way, Kanika is able to effectively and efficiently resolve this case, providing Jane her replacement cat tower and Mr. Fluffington can lounge in style. Now you might be wondering, how did that all work? And what went into that plan generation behind the scenes? The good news is if that you're familiar with our Agentforce platform already, you're already going to be familiar with the building blocks of Service Assistant. In this case, let's go ahead and take a look inside of the Agentforce builder. We're going to open up the new agent called Agentforce Service Planner Agent. And upon opening up the actual agent, we're going to navigate to the Custom Product Issues topic. This topic is meant to address issues related to custom products like the case you just saw that Kanika resolved, including any sizing issues. And all we did in here was specify in plain natural language the instructions to handle such cases for reps like Kanika to leverage. And what Service Assistant did was it matched the incoming case details to the right topic, in this case, this topic, and took the instructions and dynamically generated the plan based off of the relevant information that was presented. So all we have to do to get up and running was define some instructions, define some topics. And just like that, we can get started to generate effective and relevant plans. So that was Service Assistant. It is our newest and exciting innovation. We'd love to hear any questions that you have, feel free to leave them in the chat. And if we don't get to it, we'll be happy to reach out to you to ensure we get those answered. Let's move on to the next innovation here in Employee Service. So we're going to turn the page just slightly, but we're still going to stay focused on that employee persona and the employee lens. In this case, we're going to focus on how we can make employees more productive and work better with their HR teams. To give you some context on this, did you know that the average employee wastes about 5.5 hours per week having to manually search for information, having to do manual HR tasks themselves and jump between different systems, like Workday and their own employee hubs. So this is a very big problem, and we're excited to tackle this with Employee Service. What it is, is it's a unified AI platform that provides not only a personalized hub for employees to get everything they need, search for information, be able to manually action for themselves without having to involve HR teams, but also when they need that HR assistance, to provide our HR teams the ability to fetch data into one place, have a unified profile of their employees and be able to assist them with the next level of service. So you'll see all of this come together, leveraging generative AI, leveraging integrations with third-party HR systems. And the demo that you will just about to see will really put all this into perspective. So let's waste no time, and go ahead and dive right in. All right. So in today's demo, I'll be walking you through 2 employees. The first is Sharon, who is a new hire at Freight, Land, Air and Sea. And the second employee is Chris, who is an HR Specialist at the same company. Now Sharon, being a new hire, has a few things on her mind today. She wants to be able to learn how to request a new corporate credit card. So that's number one. And the other is, she has some questions regarding open enrollment in her insurance policy, given that she just received an e-mail on that this morning. So let's go ahead and -- Sharon goes ahead and asks the first question, which is, how do I request a corporate credit card? And right away, we see that in the Employee Hub, the answer that she's looking for is extracted right away for her with Einstein AI-generated Search Answers. The Einstein was able to pull the right knowledge for her, cite it as a source, so Sharon can go ahead and dig deeper if she needed to. But in this case, all the knowledge is already right there, spelled out for her, and she sees that, oh, in step #2, she actually needs to go to service catalog to request a corporate credit card. She goes into Service Catalog and sees the corporate credit card request. And what Service Catalog is, is it's a collection of actions categorized by topic and sorted and filtered that allow employees to take action without involving an HR specialist, saving them valuable time. So in this case, Sharon goes ahead, uses that action called corporate credit card request. Because she's logged in, all of her information is automatically pre-populated, and all she needs to do is hit Next. Just like that, the request is sent, and a case is created for her to follow up on with an HR rep. All right. That's amazing. Sharon's off to a great start. She asked her request processing. And the other question she wanted to get answered today was open enrollment and her insurance policies. So for this, she's going to interact with the Intelligent Assistant, otherwise known as Agentforce for Employee Service. Se's going to go ahead and type in her life insurance question subject. And before she begins chatting, she actually realizes she has a more immediate question regarding her PTO, and if she has enough PTO time coming up soon. So Sharon goes ahead and actually asks the Intelligent Assistant here, "Hey, can you actually check my PTO balance in Workday?" Now because the assistant is natively integrated with third-party HR systems, like I mentioned before, like Workday, it's able to pull this information seamlessly and tell her, "Hey, she has 32 hours left." Sounds like great. Now I want to request that time off. Can you actually do it for me? And wow, just like that, the Intelligent System is able to take the data that Sharon provides and automatically act on this information and request her time off. Sharon's greatly happy that this is done in just a couple of minutes rather than having to wait on hold for many, many minutes. Now Sharon goes on and she's like, "Okay, cool. I actually need to ask about my life insurance. And for this, I want to be transferred to a human specialist to serve my needs." So she goes ahead and does that. And Agentforce for Employee Service is able to seamlessly transfer her to a human in Chris to service her needs. So now this is Chris' portal, our HR Employee Dashboard. And he's able to see, thanks to omnichannel, cases that have been assigned to him and routed to him based off availability and skill set. So in this case, Sharon's case comes in, and Chris accepts it, as well as accepting the live messaging session so he can respond to Sharon in real time. Great. Now Chris takes a look at the left-hand side of his screen and sees all the information about Sharon displayed in one unified profile. This information was pulled directly from Workday so Chris doesn't have to jump around multiple systems. After reviewing the information, Chris also sees that he has other tools at his disposal. For example, things like knowledge articles. These are displayed in his dashboard, just highlighted here on screen, and Chris can reference them if there was any articles to help him solve the case. But in this case, you can see there isn't actually a knowledge article related to insurance, and we'll get back to that later. So Chris knows that the first step he needs to do is actually respond to Sharon. And he uses quick text here, which is a templatized response, to quickly send a greeting to Sharon and ask how he can help. Sharon gets the message and asks, "Hey, I need to know my options for life insurance coverage." And Chris, back in his portal sees that he got a next-best action recommended to him. This next-best action is a guided flow to help Chris learn more about open enrollment and service the case if he needed to do so. In this case, Chris says, "No, thanks. I already know about open insurance," so he doesn't need to go through that flow. Now Chris can respond, and he's going to leverage service replies. These are AI-generated responses that are grounded in Knowledge and based off the context conversation to ensure an accurate and relevant response in only a click of a button. Chris takes a look at the first response, answers the question, it's accurate, goes ahead and hits post. Sharon thanks Chris for his time and the answer, and Chris sends another service reply to close the case. After the case is closed, Einstein is still at work, being able to help generate summaries of the case. In this case, as you can see, with one click of a button, Einstein can generate a case wrap-up summary that summarizes the resolution and the issue summary and the next steps. Finally, I mentioned before how there wasn't a knowledge article for this particular issue. So Einstein can leverage the Draft a Knowledge Article functionality to be able to seamlessly spin up a new knowledge article that has everything pre-populated. So all Chris has to do is hit save as draft and publish that for the rest of his Knowledge and the rest of his service team to actually scale. Next time a service rep or HR rep comes across this same issue, they can leverage Knowledge to solve the case quicker and more effectively. And just like that, you just saw how a bunch of our different features come together to offer that endless -- seamless end-user experience for both our HR specialists and our employees, providing that next level of satisfaction for our internal teams. And so with that being said, like I said, if you have questions, please feel free to drop them in the chat. Happy to get to them. Let's go ahead and move things along. And now I'll pass it off to Will Carpenter, who's the Senior Product Manager on Field Service, to tell you all more about the innovations happening in Field Service.

Awesome. Thank you, Kevin. Before we begin, I am feeling a little under the weather today, so I hope you'll forgive me for being not on camera today, but I couldn't imagine missing this webinar. So really excited to be here today and share some of the innovations that we have coming to Field Service. I am focused on our technician persona and building innovation into our Field Service mobile application, but excited to share some of the features that we have coming throughout Field Service today. The first innovation coming to Field Service that I want to touch on that's coming in February is Data Capture. This is a brand-new way for mobile workers to collect data in the field with intelligent and dynamic forms. Data Capture is fully integrated into the Field Service mobile app, and these forms are designed to adapt to the job, making data collection seamless and efficient. With this new feature, forms are no longer a bottleneck. They can be completed with photos, voice notes, attachments and leverage device data, like location, to automate inputs. Workers can also rely on smart assistance tools like OCR for extracting text from images, voice-to-text functionality and barcode scanning to simplify the process further. Even better, these forms will soon leverage generative AI to pre-fill fields automatically based on context, natural language inputs and uploaded photos. This means less time spent on manual data entry and more time focused on the work that matters, like interacting with customers. Built for both online and offline use and powered by the Agentforce platform, Data Capture ensures mobile workers can collect critical data anytime, anywhere, while businesses benefit from faster, more accurate data collection. It's a game-changer for field operations, bringing intelligence, adaptability and ease to every job. Now this sounds pretty great, right? But let's dive into a demo to see it in action. So we're going to join Anthony, a service technician who works for a large-enterprise heating and cooling company. He's logged in the Field Service mobile app and taps into his service appointments to see his upcoming jobs for the day. He scrolls down and drills into the Work Order that needs his immediate attention. You can see our New Forms tab here. And you can see the safety checklist and service forms that are needed in order to complete this job. Safety checklists are usually the first things techs need to do before starting to work. Anthony goes ahead and launches the first form, which is all about safety on the site. As you can see, we have several input types for all needs. Input fields support voice dictations for easier input when wearing gloves or multitasking, as shown here. We've delivered 20 prebuilt components for our customers, and this is really just the beginning with this release. And within this form, you can see how deep a mobile worker can get with our conditional logic. This can turn an extremely complex form into one that is really simple for the end user, dynamically changing based on the inputs from the mobile worker and only making them input what is needed. Here, we can see toggles, text inputs, radio and check box groups, and these forms can also handle image capture and upload. In this case, Anthony can snap a picture of the maintenance history on the side of the furnace he's working on and document that for future reference. We also have a signature component so our customer can make sure their techs are signing off on important things, like safety checklists and inspections. It's as easy as tapping on the signature component and using his finger on the screen to sign off on the form submission. Now Anthony can get into the heater service form now that he's completed his safety check. And as you can see here, there are pre-populated fields that are editable. If the contact information was incorrect, Anthony could fix it in the form. We can also pull customer notes that were saved on the service appointment, and our counter components are great for picking numerical inputs. While it's important to enter data easily, entering it correctly is just as critical. The real-time input validations can help correct any wrong information right away in the moment. In this scenario, we're showing additional layers of conditional logic, asking the mobile worker if the manufacturer label is visible. When he selects yes, you can see there are now required fields about the serial number, manufacturer and year. Many companies want their mobile workers taking pictures on the job. Visual data is valuable. It adds to quality control, great for future reference and makes it easier to track progress. Sharing the images with customers can also enhance transparency and trust. But only taking images might not be enough, sometimes we need an additional layer of information. There's more to the image upload component than I'm showing here. The worker can also annotate any uploaded image. In addition to cropping or rotating, the user can draw on the image freestyle or add different shapes and texts in different colors. In this case, Anthony is able to identify the flame sensor isn't working, which is why the furnace isn't heating up. He selects flame sensor as the issue. And as you can see, an image pops up to help guide him through the process. Any image can be attached to the form, along with a description of the image. And you can see how this is a whole new medium that we're adding to the Field Service app, adding this visual media into the data collection process to provide that instantaneous visual feedback to users. We're also delivering AutoSave, which constantly saves responses as the mobile worker fills out the form. Even if they need to exit the app, take a phone call or talk to a customer, they can reenter the form and pick up right where they left off with no data loss. This is a big differentiator from the existing screen flows in the app. Long text components are included as well for Anthony to capture everything he did on site, which was a replacement part, full diagnostic, test and safety inspection. He can then sign off the work as completed. Now we know that everyone is being asked to add value to their organization. And one way for mobile workers to do that is through upsells in the field. Luckily, data capture isn't just a form that needs to be filled out. It's a guided workflow built on top of automation. No other form solution has the robust automation capabilities like we do. In this scenario, Anthony notices that a competitor has been on site to do duct cleaning, which is something he was going to suggest to the customer. Anthony can make this suggestion to the customer, snap a photo of the competitor information in the form, and an opportunity record can get created on the back end for future follow-up. It's pretty amazing, right? It shows how data capture is changing the game for collecting information in the field and making it way more efficient for end users to collect complex data when they're on the job. The next innovation I'm excited to share is Agentforce Scheduling, and this transforms your ability to schedule appointments for your customers into a 24/7 operation through agents. Scheduling Agent is a powerful new feature designed to help your organization scale by automating appointment management. This autonomous agent works seamlessly alongside your dispatchers, engaging customers intelligently and conversationally to schedule appointments within the guardrails that you define. What makes the Scheduling Agent exceptional is its ability to handle complex scenario that once required human intervention. Whether it's finding the best time slot based on customer preferences, service history or resource availability, this agent delivers a personalized scheduling experience. And with its 24/7 availability via Web chat and messaging channels, customers can book appointments at their convenience even outside of business hours. The Scheduling Agent isn't just reactive, it's intelligent. For example, if a customer requests a time slot that's already full, the agent can evaluate the importance of current appointments, identify one that is easy to reschedule and handle the change gracefully. This ensures that high-priority needs are always met without disrupting your workflow. All of this is powered by the fully connected Agentforce platform. In short, Scheduling Agent brings together intelligence, autonomy and seamless integration to deliver a scheduling solution that scales with your business while providing exceptional customer experiences. Let's take a look at a demo. So how can we deploy Agentforce for Field Service to interact with customers and help them schedule appointments more efficiently over digital channels? I'll show you how all that's possible with a few examples in action, and we'll also dive into the configuration experience. Let's first talk about exposing Agentforce directly to our customers. We're actually going to start behind the scenes, and I'll go into Agentforce Builder, where we can see how this will work. We are exposing an appointment management topic directly to our customers. We can see it reaching out to our scheduling APIs and pulling back potential booking slots for on-site work. What you don't see is a ton of dialogue trees, intent models, utterances or anything like that. One of the big advantages of Agentforce is the ability to leverage an LLM to handle the reasoning. So we're able to understand context, understand relative dates and actually get an appointment booked without hitting some confusing dialogue for the end user. This is where traditional bots fall short, and part of what makes Agentforce so unique and differentiated. These are out-of-the-box scheduling actions that you can take and use immediately or continue to iterate on for something more unique. If we see the same exchange from the customer perspective, this time we've deployed on an Experience Cloud site using Salesforce messaging. This could just as easily be over SMS, WhatsApp or any other Salesforce channel. We see our customer interacting directly with Agentforce. Again, no dialogue trees behind the scenes. Instead, we have a natural language conversation. Our agent understands the requested time frame and simply ignores irrelevant informations. Behind the scenes, it's running Agentforce Planner service, identifying the correct topic and ultimately running the action to return the proper time slots. Once confirmed, that service appointment is scheduled, and we've automated the process end-to-end and freed up a human agent to focus on more complex customer inquiries that require their intervention. Now let's look at a little bit of a different use case. What about exposing Agentforce to contractor technicians? I hear this a lot from customers that we have contractor network that is not using the app. Well, from my perspective, ideally, all of our field techs will be using the Field Service app. But if that's not possible, this is another example of where Agentforce can help. Here, we see Agentforce deployed over SMS. Agentforce can identify who is speaking based on the incoming number and serve up information about the day's schedule or jobs that the tech has been assigned. As they communicate with Agentforce, such as letting us know they're on route, the status is updated automatically by Agentforce, executing the associated actions. What about custom flows or actions that you may have built before to handle your unique use case? These can also be accessed through Agentforce. Again, what makes this so powerful is it is truly build it once and deploy it anywhere. The flows I built in the past and the other out-of-the-box Agentforce actions seamlessly work together on any channel you expose Agentforce to. In this example, it's using the post-work summary action to wrap up the job. And any updates are tracked as part of the service appointment and work order records, and we can save time and get this resource started on the next job quickly and easily. So hopefully, this demo illustrates just how powerful it can be when agents and humans work together to deliver service in the field and scheduling for service appointments. Now I'm going to hand it off to Harish to [indiscernible] And talk about monitoring for agents.

Thank you. Thank you, Will. Hello, everyone. I'm Harish Batlapenumarthy. So I'm with the Service Cloud Product Management team. I head the self-service and AI efforts as part of ServiceWorks' offerings. Today, I'm super excited to talk to you about our newest innovation with real-time supervisor monitoring. So anyone here who's used Service Cloud Omni Supervisor module already knows that we have an out-of-the-box offering, where your human agents can be monitored by the supervisors today, right? So they go in, and they're able to see what conversations the human agents are actually having right now. And as required, they can intervene and kind of take some steps. So in a similar vein, as we move to AI agents, and you've seen some awesome examples of AI agents deployed right now, both in Field Service, Employee Service and even just Customer Service, we have thousands of customers we're already onboarding right now. In fact, this week, World Economic Forum at Davos, their entire website today, any of the questions you have is powered by Agentforce. So you can go there, you can ask any questions, all of that is powered by Agentforce today, right? So super happy about it. And the question then is, as you start having hundreds of thousands of agents being deployed internally, how do you monitor them? And this is where our latest innovation comes into play. This is called Omni Supervisor real-time monitoring for agent for service. And this feature essentially brings supervisors closer to the action, providing a unified view of all active conversations, whether it's a human agent or AI agent. As you can see, we are kind of bringing them both together. And with this streamlined dashboard, supervisors can monitor every interaction real-time, right, and ensuring trust, accuracy and quality. Now what makes this especially powerful is a new feature we are adding called proactively flagging a supervisor. This will be able to proactively flag conversations that will need intervention, right? So for example...

Harish, would you mind trying to go on with your camera off because you're -- we're getting a feedback.

[indiscernible]

Yes, yes.

Hello, is this better?

No, not really. There's a feedback.

Do we refresh, or?

Can you try refreshing the browser?

Yes, yes.

Okay. Let me just try that. Hello, can you hear me?

Sounds much better.

Much better, yes?

Yes. Thanks, Harish.

Yes, sure. Sorry about that. Yes. So the point I was trying to make is that this feature is especially useful because we are able to proactively alert the supervisors when something really goes wrong. So for example, if a customer becomes frustrated and uses inappropriate language, the system can alert a supervisor to step in seamlessly, continuing the conversation without missing a beat. This seamless handoff between AI agents and supervisors ensures no context is lost, and the customers receive the support they need it d when they need it. So without further ado, I really want to jump in and show you a demo of how this really works. All right. Let's -- the demo is here. So for those who are aware, this is the Omni Supervisor page. I'm logged in as a supervisor right now. As you can see, there is a new tab there called AI agents. This is a new introduction with this feature. This is going to be available February 2025, in a month from now. As you can see, once you come here, you will be able to see all of the agent tech conversations, especially the AI agent conversations. We are calling it ASA right now. You will see all the active conversations, all the conversations that a supervisor needs to get involved with. But before we actually jump into the functionality, let's go back to see how we introduced this feature into your Agentic Builder setup. So this is the Agent page. This is essentially where you configure your agents, so if we need to bring up this agent, then open it in the Builder. So for those who are aware and who are not aware, our agents are -- the fundamental building blocks are topics, actions and instructions. Actions are what you're basically telling this autonomous agent to take on your behalf when a customer comes and asks a question. So in this setup, you can see that there are a few topics, and the new action that we're introducing for this feature is called as Raise Flag to a Supervisor. You can include this action in any topic. So I'm just deactivating the agent right now, right? And then I choose a topic called Order Inquiry. So I want to go ahead and include this action into the action library for Order Inquiry. And what that really means is, any time this bot is handling an order management topic, some customers coming in and asking questions about orders, and if there is a problem with the customer, this action will be automatically triggered. So you just add the action, then you go ahead and, at the Topic level, you add some natural language instructions, right? So this is super easy. This is really the power of LLMs that we are delivering to our customers. So you go in and put a natural language instruction and you say, "Hey, if the customer sounds frustrated, trigger this specific action, and then we'll take it over from there." That's all you got to do. You'll save this simple setup, you reactivate the agent, and then we'll just go in and see how this agent really works on when deployed on a website, right? So here's the website, and we put the agent, as you can see, to the bottom right. You can kind of invoke the agent from here. I come in here, and we'll see a simple conversation where a customer comes in, and they're having a chat with this AI agent right now. And they express a frustration that something is not really going well with their orders. What is of interest here is they can express the same frustration in different, different topics, right? It could be about orders, it could be about shipping, whatever topics you have configured. An example, there's orders. So the minute they do that, on the Omni Supervisor wallboard, you will see that flag. So that flag gets automatically kind of triggered, and a supervisor who's on this page can now see that this AI conversation is not going that well or maybe the customer is like not very happy. So how do I dig in as a supervisor? I just click in there. I can see a real-time view of what's really happening. I can even see what the bot is responding as, and obviously, it's being very empathetic when the customer expresses a frustration. So me, as a supervisor, I look at that, and it's a choice I make, either let it go. If the bot is doing a really good job and the customer does not sound super unhappy, I can let it go. Or I can take an action and, say, transfer this to a human. right? So when you click on the Transfer to Human button that you see right there, that is when the totality of this conversation, this really kind of closes the loop. This conversation now then goes into a human loop, a human queue, and the next agent, whenever they accept it, they get in the queue. And on the front end, what the customer sees is, they'll see a very seamless transfer and they'll see a message which basically says, "Hey, this conversation is now going to be transferred to a human, please wait in the queue." So it's -- from the back end, it's super real time for the supervisor to intervene. And from the front end, it's very seamless for the customer, and they're fully kept in the loop, and they're informed when said, "Hey, this is going to be going to a human agent now," right? So that is a new innovation coming in. There's a bunch of others as well, but this is one of the primary things that we wanted to kind of surface for you because the future of all these Agentic experiences is that AI agents and human agents are going to coexist. And how do we, at Salesforce, bring in innovation when this coexistence happens? So this is one of the many that are coming down the road, and we are happy to take any questions as well. Now this slide is where I'll talk about a few road map items. Clearly, if you look at all the pillars in Service Cloud, all the innovation that comes in, both Kevin and Will have already spoken about some of the flagship features that we are already releasing right now, but there's a lot more coming down the road. So I just wanted to talk about a few of them. Like on the self-service side, you already saw the Supervisor Monitoring piece. The other piece that's coming up is we already have the Agentforce for Service Agent that's already out there for real-time conversations. So there is an autonomous bot talking to your customers on the website and the mobile app on Facebook, on WhatsApp, whatever channel you want, it's already available. It's GA right now, and we have lots and lots of customers doing that. But the next logical question is, hey, what are you going to do? When can this autonomous conversation happen on an e-mail channel, on a voice channel? So that's coming down the road. In February, the e-mail piece is going to be available as a public beta, and it's going to be GA in June 2025. What this really means is when a customer e-mails in to a support@by.com, whatever your e-mail address is, once this is configured, the exact same engine, the logic engine, the AI engine is going to respond to that autonomously until the point customer kind of says, "I want this to be handled by a human rep," which is when it will get escalated to a human rep. And all of this is going to happen on your -- our most beloved case object. So none of this is happening in some -- either/or some other new object. Everything is going to be tied to the case object. So when such an autonomous e-mail comes in, you go query the case it creates, you will see the entire interaction of how the AI agent has been responding. And when it goes to a human agent, how are they responding? You'll be able to see all of that in the agent console. So that's coming in June as a GA. And then the voice channel is going to be available by sometime later this year, most likely by Dreamforce. So the dates are still tentative. Again, the idea is somebody calls in, this is the most demanded request from a lot of our customers who are using it right now, using Agentforce right now, which is how do we do the same thing on voice. So somebody calls in, can the voice bot respond to them as intelligently as you can see today with a textual conversation, right? The other beauty here is that, I think Kevin talked about it, which is build once, deploy anywhere, it's the exact same concept. Whatever agent you're right now building, it's going to work with the exact same configuration on any channel you want to deploy it, whether it's WhatsApp, whether it's Facebook, your mobile device or voice or e-mail, it will work with the exact same setup. You don't have to change anything. So there's a massive innovation coming in Self-Service. Same thing with Portals. If you're using our Self-Service Portals, we would highly encourage you to do that. There's a next-gen portal coming in where you'll be able to do a bunch of AI-powered features, whether it's a knowledge summary, an automatic article summarization on the portal itself, being able to kind of dynamically design your portal with just natural language text, a feature where your search in the portal will automatically get transferred to the agent itself. A bunch of these features are also coming this year. From a channels perspective, we already talked about voice. That is a real big deal from a channel angle. Assisted Service, I think Kevin talked about service plans. There is a basic question that's coming out right now. But in June, we're going to have adaptive plans. What that really means is the first guidance plan that was generated by the AI engine, now that will get dynamically updated as new information comes in, right? So as the case keeps getting updated when the customer responds and there's newer information comes in, a newer plan will be suggested to the rep, who can then choose to kind of execute that plan or kind of change from the plan. In addition, if there's a newer plan, let's say, there are like 7 steps in there, and if the human rep kind of says, "Okay, the 4 can be automated, why don't you go ahead and automate those?" Our system, this service plan system is going to automatically autonomously execute on those steps as well. So that innovation is coming for our Assisted Service pillar down the road. The other piece I want to talk about is Field Service, right? So this is essentially where a lot of really cool stuff is shown by Will, but there's one piece about asset prediction, right, where we leverage data from connected assets to anticipate when service may be needed before an issue actually occurs. This will help you reduce downtime and increase revenue from preventative maintenance. The other piece here is about multimodal support. This is not just for Field Service. This is going to come for every service interaction, sales interaction. So this is a very generic feature across all of our Agentforce. And the idea here is how can this AI engine autonomously evaluate any multimodal input, right, whether it's coming through an image or a video, audio. How can this AI engine -- I think ChatGPT already does something like that. So we are bringing that to the entirety of Salesforce. So that comes in when an image comes in or a PDF or audio/video, how can the engine analyze that, and then intelligently talk back to the -- whether it's a customer or an internal Field Service technician or maybe a sales rep, how can we analyze this kind of multimodal inputs, but still be talking to that intelligently. So this is a huge, huge deal. Initially, obviously, it's coming to Field Service, but you will see this being adopted across almost all Salesforce properties as well. And lastly, with the Employee Service, we already went GA last year, late last year. We're going to have a new Employee Service agent, which is going to be deployed on the portal. Just like you'll see the customers-facing customer agent, the autonomous agent. You're going to have an Employee Service Agent also available by February. There will also be some deep integrations to Workday. So for any of our customers who are common customers of Salesforce and Workday, this is going to be all available out-of-the-box, right? So come in, configure this. And for your employees to be able to ask questions about, hey, what's my PTO? How do I submit my PTO? I want to update my employee details. This autonomous agent is essentially going to do all of that, will significantly reduce any of your in-house cases or costs coming in. And of course, there's a lot of other stuff as well we are happy to share, but these are some of the highlights. This is where I'll pass it on to Rebecca and happy to take any questions.

So thank you so much, everyone. And the audience, you can see that there's a lot coming. We've covered some of the highlights, and we've even covered some of the longer-term road map. So the team are very busy. Thank you, and appreciate you taking the time and dialing in from the U.S. So look, we -- earlier on, we talked about the release notes. Again, this is a very, very detailed information on all the product features. I believe that we've got a link to that, so you can actually access that. And then the release website and release trailheads are coming soon, so watch out for those. The release website provides lots of useful information. It's a bit of a high-level overview of the key innovations and the release trailheads, part of the Trailhead. I'm sure you've all jumped on those. But again, it's interactive, self-paced learning. You can get some trails and badges. Again, more information coming on that. For those of you that are local and would like to attend Agentforce World Tour Sydney on the 26th of February, you can scan the QR code to register. We will be talking about all of our product innovations in depth, and you'll actually have the opportunity to get hands on with some of these products. So definitely worth a visit. And then we have a brand-new local e-book, which features local customers and give you some real hints and tips and tools for building your business case for AI and Agentforce. So again, another great tool that you can download. We are going to pass -- we are now going to move on to some Q&A. We've had a lot of questions come through. I know that the team are busy trying to answer as many as they can. But if we don't get to all of them today, we will follow up with answers to all of your questions. Okay. So I'm going to open it up to Q&A. So my wonderful PMs, if you'd like to come on screen, will you stay off screen because I know that you are having a bit of a breather and a bit of a rest, but let's jump in with some questions.

Okay. So Kevin, let's start with you. Simple question, how can I get Service Assistant?