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

Good morning, everyone. Welcome to today's session, Service Cloud Spring '25 Release Highlights. Thank you all so much for joining. My name is Natalie, and I'm on the corporate marketing team here at Salesforce. Before we begin, I would like to cover a few quick notes about our webinar platform. Today's webinar will be available on demand after we wrap up and will be accessible through the URL that you're on now. Please note the slides will advance automatically throughout the presentation. To enlarge the slides, click the enlarge slides button located in the right-hand corner of your presentation window. Should you need technical assistance, click on the help widget located on the bottom left corner of your console. We've also added some additional resources, which are available through the resources window to the right of the slides. There, you can find additional related content. And lastly, we encourage you to submit questions at any time throughout our presentation using the Ask-A-Question widget at the bottom of your console. We'll get to as many questions as we can at the end of our session. And with that, I'm going to hand it off to John to get us started.

Awesome. Thank you, Natalie. All right. Welcome, everyone. Good morning, good afternoon, good evening, maybe. Yes, welcome. We're happy to have you for the Service Cloud Release Highlights. So this is actually a new motion for us, and we're really excited to share this information. But we would love any feedback from you all afterwards to let us know how we can improve or make this session more informative and helpful. So to start this off, thank you so much. We really appreciate you taking the time to join us today. We know everyone has busy schedules and jobs and is doing a million things. So we appreciate you and the Salesforce community that's always dedicated to learning and spending time with us. All right. And a quick note from our legal team. So we're going to be showing a lot of our future innovations. And we just want to make sure that you're making purchasing decisions based on what's currently available. All right. Now let's meet our amazing presenters. So I'm John Capalbo, I'll be your MC host for today. I'm part of the Service Cloud product marketing team. I've been in the Salesforce ecosystem for over 10 years now and have been part of Salesforce for the last 5. We also have 3 amazing product experts joining us, which will be giving us a deep dive into the -- our top innovations for spring '25 and presenting product demos. So we have Kevin and Harish from the Service Cloud product management team and Will from our Field Service product management team. And I'll let them introduce themselves a little bit later when we get to their sections. Okay. So just to quickly level set on the Salesforce's release schedule. So 3 times a year, we have a release and this is usually -- or this is aligned to our seasons. But I mean if you're not in the U.S., the seasons don't always make sense. So I thought it would be a good way just to present out, hey, what you can expect throughout the rest of the year. So the spring '25 release goes GA in February, so that's what we'll be talking about today. We have our summer release in June, and we have our winter release in October. So just about a month before each release, we have a release preview. So this is all of the content and release notes that are made available ahead of time, so you all can prepare and learn about those new innovations that are coming up. And I'll go into more of those resources and what's available now for you to learn more about this upcoming release later in the presentation. All right. Now for good, old -- my Service Cloud's pitch here. So Service Cloud is the most complete platform to enable companies to help manage -- or to manage service or all types of service. So this is from self-service, contact center to field service across all channels and for all industries. So we have AI agents powered by Agentforce to help automate key support experiences and seamlessly hand off to human agents with full context. And by having AI in the flow of work, you're making your service teams more productive and boosting higher -- also driving higher customer satisfaction. And to top it off, these capabilities are all powered -- are all built on the Salesforce platform with Data Cloud and Agentforce. But let's get into kind of the meat of this presentation, so what we're actually going to be covering today. So we picked out the top 5 innovations that we think are going to be the most impactful for this spring release. So we've got Service Assistant, which is built into the service console to help your service reps be more productive with AI. We have a new offering, Employee Service. So this is going to help your HR teams seamlessly manage internal employee support. Then we have data capture forms for the Field Service mobile app, which is going to make your mobile workers more efficient with dynamic and intelligent forms. Then we have Agentforce scheduling for field service operations, so this is going to improve your customers' self-service scheduling with AI-powered appointment booking. And then we'll get into real-time monitoring of agents, which is in Omni Supervisor. So your supervisors have real-time visibility into those AI agent conversations and can tap in and help improve that quality of service. So yes, this is covering what we're going to get into. We'll deep dive into all these features. And to kick us off, I want to hand it over to Kevin to get us started.

All right. Thanks, John. Hi, everybody. My name is Kevin Qi. Excited to be here with you all today. I'm an associate product manager here on the Service Cloud team at Salesforce and super pumped to walk you through some of our exciting innovations coming out very shortly. So let's go ahead and dive right in and we're going to kick things off by telling you about what Service Assistant is and the amazing capabilities it will bring. So as its name implies, Service Assistant is your trusted AI assistant that helps service teams close cases faster and more effectively. The first capability that Service Assistant will be able to do that is going to be generally available is the ability to generate relevant step-by-step plans for service reps to tackle a case from start to finish. The plan is going to be grounded with all the case context, relevant details of the engagement history and be super relevant to the particular issue at hand, so that a service rep can follow the steps and ensure that they're not missing any important information. It's not only great for your new reps that are just now onboarding or finished onboarding and still are learning the ropes. But also there are very seasoned representatives that might just make sure that they're not missing anything or keeping up to the updated guidelines. And so instead of me telling you about this, let me go ahead and dive right in and show you what Service Assistant will bring through a demo. All right. So in this demo, I'm going to be walking you through a day in the life of Kanika, who is a customer service representative at WhiskerWorks. Now WhiskerWorks is a pet supplies company who specializes in custom pet products for all your furry companions. And today, Kanika opens her service console to see that she has a customer case from Jane Hammock, who's inquiring about a sizing issue with her custom cat tower for Mr. Fluffington, her beloved 20-pound Maine Coon cat. Unfortunately, it looks like the tower was too small for Mr. Fluffington, and before Service Assistant, Kanika would have had to read through all the details, extract the key information and piece together a plan. But now that is no longer the case, thanks to Service Assistant. As you see on your right-hand side of your screen, Kanika sees that Service Assistant has generated a plan for her to tackle the case and gives her a high-level summary to digest and get caught up to speed. Kanika hits draft plan, and voila, just like that, a step-by-step plan is generated that's personalized for Kanika to solve this case. The first step is to gather information. Kanika sees that she needs to confirm the order ID, which was automatically extracted by Service Assistant. And she also needs to get some additional information from Jane, including some photos and some additional dimensions to actually verify that there was indeed an issue. Thanks to Service Assistant being integrated with our Service Cloud platform, Kanika can act on this right away. She goes and uses the service e-mail feature and draft with Einstein chooses a pre-configured template to help gather information. And just like that, in a couple of seconds, Einstein generates a thoughtful e-mail in the brand voice of WhiskerWorks that also asks for the information in which Kanika needs. Kanika reads the e-mail, everything looks great and she does not have to type a single additional character, goes ahead and hits send. Now Kanika can check off the first few steps of the plan. And just like that, she's already on her way to resolving this issue. Kanika reviews the information that Jane sends back, cross-checks the product ID internally with the internal teams and actually realizes that indeed a manufacturing team did make an error here. No worries. Service Assistant guides Kanika to offer a replacement tower for Jane at no additional cost and Jane gladly accepts. So Kanika proceeds to generate the tracking information and get back to Jane. Now last but not least, WhiskerWorks has a company policy to always send a resolution e-mail to the customer, summarizing what happened, the resolution steps and also recommend similar products that might go well with the customer to help them with cross-selling. In this case, Kanika goes back and utilizes the same flow as before, but this time selects the close case e-mail template and waits a couple of seconds to see a thoughtful email that not only summarizes what the steps Kanika took to solve the case were, tracking details, but also the similar products that might go well with her cat tower. In this case, wall-mounted shelves, scratch pads and just another way to offer an elevated service. Kanika goes ahead and hits send and is able to check off the final step of the plan and close it out, effectively resolving the case. And thanks to a Service Assistant in guiding her each and every step along the way, Kanika is able to confidently and efficiently resolve this case. Jane gets her replacement cat tower and Mr. Fluffington can lounge in style. So now you might be wondering, how did that happen? What went into generating that plan? Let me take you behind the scenes. If you're already familiar with our Agentforce platform, this might be not new to you. We're using the same foundation for Service Assistant in topics, instructions and actions. So let's go ahead and pop open a new agent inside of Agent Builder called Agentforce Service Planner agent. And in this agent, we're going to go into the custom product issues topic. This topic was what was used to actually generate that plan. We give this topic instructions and a description to tell Kanika and other service reps how to resolve these kinds of cases. Service Assistant then dynamically matches the case context with the right topic and pieces together the right instructions to show based off of what information exists. And the best part is all of this is written in plain natural language so you can get up to speed and write effective plans in just minutes. And there you have it, you just saw how Service Assistant works effortlessly across our Agentforce platform and our Service Cloud platform to really offer that next level of customer service and improve the experience for our end customers. If you have any questions on any of that, feel free to send it in the chat, as we mentioned. If we can't get to it in this session, we'll definitely reach out -- your AEs will reach out to you and we'll get those questions answered. All right. So now let's go ahead and pivot slightly, but stay on that employee lens. We're going to be talking about how we innovate within internal organizations with HR teams and how employees interact with them. Before I do that, I want to ask you all a quick question. Did you know that the average employee loses about 5.5 hours a week just from having to do mundane task like look for information, to perform manual HR tasks by themselves and also jump between different websites or systems like Workday and their own internal hub. This is a big problem. And so we launched Employee Service in order to tackle this and offer a unified platform that's integrated with AI and third-party HR systems to help elevate our -- give our employees back time. And in this case, employees will have a personalized hub where they can go find answers using generative AI and be able to get what they need without having to involve HR specialists. Then on the HR side, we empower reps to have the ability to look into a unified view of our -- of their employees and better service them with real-time data. Just like before, let's go ahead and show you rather than tell you. And so let's go ahead and hop into the demo. All right. So in this demo, I'm going to walk you through the day in the life of 2 employees this time. The first is Sharon. She is a brand-new onboarded employee at Freight, Land, Air and Sea. And the second employee is going to be Chris who is an HR specialist helping service some of Sharon's needs. So we'll go to Chris later. For now, let's focus on Sharon. Sharon has a few needs today. She just onboarded and she wants to get a new corporate credit card. So that's number one. She also has some questions about open enrollment regarding her life insurance. So just go ahead and tackle the first question. How do I get a corporate credit card? Sharon asked the question in the employee hub, and right away, we see that Einstein gives her the answer she needs as well as relevant knowledge articles below. But in this case, all the information is extracted for her, put in front of her and she just needs to read and get the knowledge that she needs. There is a source that's included with this answer in case Sharon needs to go and dig deeper. But in this case, that's not necessary. Step two actually tells Sharon that she needs to go into the service catalog to request a corporate credit card. So she navigates there, sees that she does see the action to request a corporate credit card. And the service catalog is really a library of actions that employees can take without having to involve an HR specialist. So they can self-serve really effectively, and Sharon does just this today. So she goes in, clicks on request corporate credit card. And because she's already logged in, all her information is prefilled out. She just has to review it, hit next, and just like that, a case has been submitted to the HR team to service Sharon's request. Now that was really seamless and amazing and Sharon is already excited about her day. The next thing she has to do is she has some questions about her life insurance policy and open enrollment and she wants to reach out to get some information. So in this case, Sharon reaches out to the Intelligent Assistant, otherwise known as Agentforce for Employee Service to get some answers. Now before she does that, she realizes, oh, she actually has an immediate question about her PTO time next week and coming up. So she goes ahead and first asks, hey, can you actually tell me if I have enough time for PTO? And she goes in and asks that question. And because the Intelligent Assistant is integrated with Workday, is able to pull that information back and give Sharon the immediate answer. But not only tell her, it can also act on this information. So Sharon wants to at least -- Sharon wants to actually take that time off given that she has enough here and goes ahead and provides a date. And just like that, the Intelligent Assistant is able to actually schedule that for her. So Sharon doesn't have to take another step. Pretty exciting. And now Sharon moves on with her main question about open enrollment and her insurance. But for this, she wants to be escalated to a live human specialist. So Agentforce for Employee Service seamlessly transfers to a live agent. And in this case, let's go ahead and look at Chris' point of view. So this is the employee dashboard for Chris as an HR specialist. And he leverages omnichannel, which dynamically routes work items to the right service reps based off availability and skill. And here he sees Sharon's request has been pushed to him. So he's going to accept both the case and the live messaging session so that he can respond in real time with Sharon. Great. Now on the left-hand side, Chris sees that all the information with Sharon is already pulled for him and displayed on screen. This information was pulled from Workday and all natively integrated, so Chris doesn't have to hop around and find the key information about Sharon's profile. He also has another -- he also has a couple of other tools at its disposal, including knowledge. Here, as you can see, he can reference knowledge articles to help get up to speed on common questions and relevant questions for this case, just like how Sharon would on her employee hub. In this case, it looks like there wasn't any knowledge articles relevant to open enrollment at this time, and we'll get back to that later. So first step Chris needs to do after reviewing the profile is to respond. Chris utilizes Quick Text, which is a templatized response to quickly respond and greet Sharon and ask her how he can help. On the other end, Sharon gets the message and replies saying, I need to get insurance questions. Chris then sees a next best action automatically displayed at the very top. This is a guided flow that can help Chris learn more about open enrollment if he didn't already and provide more information to help solve this issue. Now in this case, Chris already knew kind of the high-level detail, so he doesn't need to leverage that flow. And to proceed, Chris utilizes Service Replies, which are generated replies grounded in knowledge and the context of the conversation to formulate an accurate and relevant response. Chris reads the first service reply, sees that it's accurate and it covers all the information regarding open enrollment, goes ahead and sends that over in just the click of a button. Sharon gets back, says thanks and Chris uses another service reply to respond and close out Sharon's case. Even after the case is closed, Einstein is still at work, in this case, helping summarize that resolution and what the steps were to help get it to a closure. So Chris goes ahead, hits save. Just like that, he has resolved it and summarized it. And remember how I mentioned there wasn't a knowledge article before to help solve this issue? Well, let's change that. With Einstein Knowledge Article creation, in this case, we can leverage AI to create that knowledge automatically and provide that scale and growth of knowledge for future agents and future HR specialists to resolve similar issues down the line. And so just like that, Chris goes ahead, submits that knowledge article and we are well on our way to scaling our HR teams and saving time. So that was a lot of information in what you just saw. But what's really powerful is all those features coming together to offer that end-to-end experience for both our employees and our HR specialists. Like I said, if you have questions, feel free to drop them below or reach out, and we're happy to answer them. With that being said, I'll now hand it off to Will Carpenter, who will walk us through some exciting innovations in field service.

Awesome. Thank you, Kevin. Yes. So my name is Will Carpenter, I'm a Senior Product Manager on the Field Service team. I'm excited to share some of the innovations that we've been working on. My focus area is on our technician persona, so bringing innovative features into the Field Service mobile app. We're going to be covering a couple of different areas throughout Field Service today. The first one that I'm really excited to announce this coming in February is Data Capture, which is a brand-new way for mobile workers to collect data in the field with intelligent dynamic forms. Data Capture is fully integrated into the Field Service mobile app. So these dynamic and intelligent forms are designed to adapt to the job, making data collection seamless and more 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 texts 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 entry and more time focused on the work that matters. Built for both online and off-line use empowered 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 intelligent adaptability and ease to every job. Let's take a look at a demo of Data Capture in action. So let's join Anthony, a service technician who works for a large enterprise heating and cooling company. He's logged into the Field Service mobile app and taps into his service appointments to see his upcoming jobs for the day. He drills into the work order that needs immediate attention that he sees on his schedule list. And here, you can see our new forms tab. When he taps into this tab, you can see the safety checklist and service forms that are needed in order to complete this particular job. Safety checklists are usually the first thing techs need to do before starting the work. Anthony goes ahead and launches the first form, which in this case is all about safety. As you can see, we have several input types for all needs. Input field support voice dictations for easier input when wearing gloves or multitasking like we're showing here. We have delivered over 20 prebuilt components for our customers. 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 a simplified one, dynamically changing based on inputs from the mobile worker. Here, we can see toggles, text inputs, radio and checkbox groups. And these forms can also handle image capture and upload. So later on, we'll see Anthony capturing an image of the service history that's documented on the side of the asset in this case. He snaps a photo and it's attached directly to where it needs to go. Now Anthony can get into the heater -- or excuse me, with our signature capture component, our customers can make sure their techs are signing off on important things like safety checklist and inspections. So here using his finger, he can just sign off on the form, and we know that he's completed the safety checklist and can proceed with the work. So now the safety checklist is complete, let's move on to the heater service form. As you can see in this form, there's a bunch of pre-populated fields that can be edited if needed. In this case, the contact information might not be up to date for the users -- for the customer so Anthony can fix that directly within the form. We can also pull in customer notes that were saved on the service appointment. And our counter component is great for quick numeric inputs here. While it's important to enter data easily, entering it correctly is just as critical, right? And the real-time input validations can help correct any wrong information right away. 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 new required fields about the serial number, manufacturer and year that he has to fill in to proceed. Many companies want their mobile workers taking pictures of the job. Visual data is valuable. It adds to the quality control for future reference while making it easier to track progress. Sharing the images with customers can also enhance transparency and trust, but only taking images might not just be enough. Sometimes we need an additional layer of information. And there's more to the image upload component that I'm showing right now. The worker can also annotate the uploaded images. In addition to cropping or rotating, the user can draw on the image free style or add different shapes and text and different colors to indicate important content on the image. Anthony is able to identify that 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 them through the process. Any image can be added to the form along with a description that helps -- assist mobile workers in completing of jobs. We're also delivering auto-save, which constantly saves responses as the mobile worker fills out these forms. Even if you need to exit the app, take a phone call or talk to the customer, they can reenter the form and pick up right where they left off with no data loss. Long text components are included as well for Anthony to capture everything he did on site, which was a replacement of the part in this case, a full diagnostic test and safety inspection. He can then finish out by signing off on the work again using the signature component again. And as we know, everyone is being asked to add value to their organization, and one way for mobile workers to do that is through upsells. Luckily, data capture isn't just a form that needs to be filled out, it's a guided workflow built on top of automation. In this scenario, Anthony notices that a competitor has been on site to do duct cleaning, which is something that he is going to offer and suggest to the customer. Anthony can make the suggestion to the customer, snap a photo of the competitor information in the form and an opportunity record can be automatically created on the back end for future follow-up. Pretty amazing, right? It shows how data capture is changing the game for collecting information in the field. Next up, I'm excited to share Agentforce scheduling, which transforms your ability to schedule appointments for customers into a 24/7 operation. Scheduling agent is a powerful new feature designed to help your organizations 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 scenarios 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 in the future, 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 could be rescheduled to a later date 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 that's all possible with a few examples in action. Let's first talk about exposing Agentforce directly to our customers, like we talked about with the scheduling agent. Let's dive in behind the scenes and I'll go into the Agentforce Builder, where we can see how this will work. We're 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 here 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 confused dialogue. This is where traditional bots fall short and part of what makes Agentforce so unique. 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 exact same exchange from the customer perspective, this time we've deployed on an experienced 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 and our agent can understand that the requested time frame and simply ignores irrelevant information in the conversation. Behind the scene, it's running the Agentforce Planner Service, identifying the correct topic and ultimately running the action to return the proper time slots. Once confirmed that the service appointment is scheduled and we've automated the process end-to-end, we've freed up a human agent to focus on more complex customer inquiries. 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. Their contractor network is not using our app. Ideally, all the field techs will be using the app, of course. But if that's not possible, this is another example of where Agentforce can help. Here, we're seeing Agentforce deployed over SMS. Agentforce identifies who is speaking based on the incoming number and serves up information about the day schedule and the jobs that the tech has been assigned. As they communicate with Agentforce, such as letting them know they're on route, the status is automatically updated by Agentforce, executing the associated actions. For custom flows or actions that you may have built before to handle unique use cases, these can also be accessed through Agentforce. What makes this so powerful is it's truly build it once and deploy it anywhere. The flows that you've 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 using the post-work summary action, the technician is able to wrap up the job using the LLM to generate a draft of the summary. Any updates that it makes -- that the user makes through Agentforce are tracked as part of the service appointment and work order records and can save time and get these resources started on the next job quickly and easily. Pretty impressive, right? So we've taken a look at how Agentforce is really changing the game in the field service realm. I want to pass it off to Harish to talk about the next topic, which is monitoring these agents for Service Cloud across the board. Harish?

Thanks, Will. Hello, everyone. I'm Harish Batlapenumarthy, I'm a Senior Director in Product Management at Service Cloud. I essentially own all of our self-service products here in Service Cloud in Salesforce. Super excited to talk about all this new innovation that's coming up. I will be touching upon real-time monitoring of agents. So just to give some brief background for this, we went GA with Agentforce Service Agent in October. So right now, we have lots and lots of customers who have actively deployed this customer-facing agents. They're getting a lot of feedback -- we are getting a lot of feedback, very strongly positive feedback on how they're using it. So this new innovation that's coming up is essentially extending our current capability in the Omni Supervisor module, where you'll -- where today you're able to monitor. As a supervisor, you're able to monitor all the human agents, human reps and kind of helping them real time if they're stuck with anything. That feature is now extended to AI agents as well. So you have one single wallboard where a supervisor would be able to monitor all conversations, whether it's human or AI agents, and they will be able to jump in real time to kind of help with this, right? So -- and with this streamlined dashboard, they're able to make significant changes if required. If there is a frustrated customer who is kind of really unhappy and the AI agent is kind of doing this empathetic response, you want a human supervisor to jump in and take over the conversation or redirect it to somebody -- some other human agent as appropriate. So with this new feature, we're introducing that functionality as well. So I'll kind of jump in with the demo itself and kind of help you visualize how this really works. And as you can see in this demo here, I am a supervisor right now. I'm on the Omni Supervisor wallboard. And as you can see, a new tab that we've introduced called AI agents. So this is a new tab that you're going to see. Once you click on this tab, what you're going to see is all the different agent conversations that are happening right now in real time as a supervisor, right? So I'm able to monitor how many agents are actually conducting these conversations. As you are aware, most likely, you can deploy multiple agents and every one of those agents will be monitored here. And within each agent, you'll see I'm able to actively monitor these agents. So let me just take you back to the actual agent configuration itself. So this is how you define an agent today. You can open up the Builder. This whole functionality is powered by a new action called Raise Flag to supervisor. So what you really want to do is be able to add that action to any of your topics in your agent conflict. As you can see in this specific agent here, we have various topics. I want to go ahead and add this to the topic called order inquiries, right? So if you have already configured this in any AI agents in the Salesforce, this should be straightforward and very easy. If not, this is essentially how we do it. So you first deactivate the agent, you pick that topic. Each topic has topic instructions as well as actions. So we go ahead and add this action. So we already prebuilt this action. When you upload -- when this feature becomes GA, this action is going to be available in the action library. You go ahead, you add this action, you're able to customize it as well. But here, you just add instructions to the topic. So the way Agentforce agents work is that these are all natural language instructions, just like Kevin was talking about earlier, where we configure a different agent. But here, for this agent, we are adding this action. We are putting the instructions saying, if anything goes wrong with a customer, trigger this action and then go automatically flag a supervisor. So I then reactivate the agent. So now this agent should be able to do this flagging as well. So let's go from here to a web portal where this agent has been deployed to the bottom right-hand side, as you can see. I click it open. I start the agentic conversation. A customer, let's say, comes in, right, and they are frustrated that one of the orders they received is not exactly up to their expectations. So they come in, they do this. In today's world, when this happens, the AI agent responds empathetically, but a supervisor really doesn't get to see it. But with this new feature, you will see on the supervisor wallboard a flag, right? So this flag is going to show up and the supervisor is going to look at this flag, they understand this conversation needs attention and this is coming from an AI agent, right? So they can actually dig in to this conversation. I can now click in and monitor in real time, live, I'm able to see exactly what the agent -- AI agent said and what the customer said. And if I decide as a supervisor that I want to intervene, we intervene. We start -- we can click a button that is saying transfer to a rep. This is essentially how you take this entire conversation, move it from the AI agent to the human rep and just queue it up for them and move to the human rep and who then takes over from there. So this is a new feature. We are very, very excited that we are now able to pull in AI agents into human rep monitoring as well. There's a lot more functionality coming in this well -- in future releases and we are happy to take any other questions for this. So we will now move on to a road map discussion where we want to really share in all of 4 pillars various road maps that we are coming up with. And we just move to the next slide. So today, we presented a bunch of innovations here. These are all the various pillars in Service Cloud and the associated teams here. In the self-service pillar that we just talked about, you saw the supervisor monitoring piece is already coming up. But the other critical things we want to talk about is that there are lots and lots of asks about when is this Agentforce Service Agent, the AI agent, when is that going to be available on new channels or surfaces? The one that is GA right now is purely for conversations and chats. What's coming is for e-mail. So the e-mail conversations will be first beta in February. And in June, it's going to be GA. The idea here is that when somebody e-mails in, can the AI -- kind of Agentforce AI, can it autonomously respond to that e-mail, right? Just like it does today on the chat or conversational channels, can it do it on the e-mail channel? And absolutely it can do that, and that's coming very soon. The other exciting thing is that anyone who's already configured the self-service portals, you'll probably have a Salesforce portal out there. You will now be able to pretty soon, sometime this year, we will be having a generative portal included that you're able to come in and Agentforce AI is going to help you actually with the portal using natural language. There's a bunch of other innovations as well, I just wanted to highlight this here. From a channels perspective, we want to talk about once this Agentforce agents be deployed channels, is there a way for you to collect service feedback, right? So that's also coming up. This is a big conversation service. You'll be able to actually deploy this and you can have the survey question going back to your customers in a conversation. The other channel associated that's going to open up is also voice. It's a very, very in-demand ask. We've a lot of customers who are very excited about Agentforce for conversations. They also want the exact same autonomous agentic response on voice. So e-mail is coming up in June. Voice is going to come up around Dreamforce, around October the time frame and we are going to have that. From an assisted service standpoint, Kevin already talked to you about the Service Assistant, which is going to be GA pretty soon. We are going to enhance the capability there because today what Service Assistant can really do is give you a guidance plan, right? But in June, it's going to become much more dynamic. It's going to take -- it's going to be able to take real-time updates on the case and dynamically generate a new plan, right? So that's essentially what we're calling them adaptive plans, and that's coming up in June as well. From a Field Service standpoint, in addition to what Will has already presented, asset service prediction, which is GA in Feb '25 that [indiscernible] data from connected assets to anticipate when the service can be needed before an issue occurs. This will help you reduce downtime and increase your revenue from [indiscernible]. The other super exciting piece, which is not just for Field Service, it's going to be applicable for across a lot of our other clouds as well, which is multi-modal analysis for agents. In this specific example for guided multi-modal computing, this will allow you to deploy Agentforce for technicians when they encounter an issue in the field. By using images and text, mobile workers can chat with Agentforce to convey their problems and Agentforce will use their data and knowledge to walk the technician in solving the issue. The core idea here is that today, most of the interactions are on the text modality. But when a customer wants to upload an image, can the Agentforce agents automatically process that and have an intelligent conversation back and forth. So this is coming for Field Service, for sure, but this capability is going to be available across the board around the [indiscernible]. And then lastly, on the Employee Service piece, I want to talk about our integration with Workday. So this is coming up pretty soon as well where if you are a joint Salesforce and Workday customer, the employee service agent is going to be a new -- is going to come up for a purely internal employee service use cases. This can now access any of the Workday data. Any questions like, hey, I want to give my PTO or I want to submit my PTO? Instead of going through some form -- workflow experience, we can now start doing it conversationally right from within the Employee Service agent. This is also coming up in Feb '25. So as you can see, there's a lot more innovation coming up. We are happy to share what's happening in a variety of fora and variety of channels. But this is where I'll transition over to John.

Awesome. Thank you, Harish. That -- yes, I love that road map slide. It's really awesome just seeing all of the innovations that are coming out throughout the year. I mean, that is just jampacked. So a lot of exciting stuff for you all to look forward to. And we will be having this release going -- or this release webinar going forward so you'll get to learn about it from us in the future. So I wanted to quickly just touch on those resources that I mentioned earlier. So how can you learn more about this upcoming release and future releases? So first off, we have the release notes. So this is going to be really the most in-depth place where you can get key details about every feature that's coming out across Service Cloud and other clouds. So this is going to be key information like, hey, what licensing do I need for this feature? How do I set it up? How do I configure it? So a great resource to look through. We have our release website as well. So this will be updated and include what's top of mind or what we're thinking as top of mind for each of the clouds and for the specific releases. So it will have our release highlights. It will have links to the other release resources and give you a great place to start and learn more about our innovations. And then we have our release Trailhead. So Trailhead, our learning module, you can interactively learn and earn badges about our spring release and dive into more feature-specific trails to learn more and get you up to speed. So awesome resources beyond the lookout for those going live soon. And then we would love to stay connected with you all. I mean, this is such an amazing community and you all have so much experience and expertise within your companies and with Salesforce. So we'd love for you all to join our Serviceblazer Community on Slack. So this is where we connect like-minded professionals. It's a great place to learn, ask questions, share experience and grow your career. I mean, we are part of this from the Salesforce side as well. So you'll get questions answered from employees at Salesforce as well as others in the industry. So just a really great place to connect and stay informed and learn about best practices. Awesome. Well, thank you so much for joining us today. I really hope this was informative and helpful and gave you a little bit of insight into what's coming out and what's -- what our future holds. Really happy to have you. And we have some extra time here where we can start fielding some Q&A. So please feel free to submit any questions. Anything we can't answer today or run out of time for, we'll follow up or your account managers will follow up and be able to get you that answer.

So I'll go ahead and tee up some that we had come in here. Let's see. Okay. So this one is for Kevin. For Service Planner, is a service agent able to save their progress in the completion of a service plan? I only noticed a close button. What happens when they close out the tab while waiting for a customer reply?

Yes, that's a great question. The answer is yes, the service plan once it has been generated is saved and persisted on to that case. And also, when check boxes have been done, so say some steps have been completed, the service rep is working through it and they navigate off the page or they close out the tab, those updates are also saved to that case. So it's very powerful for when service reps are handing off cases to one another. Maybe they want to see what steps have already been completed. All of that is persisted, and even then, also in progress bar gets updated, when a plan has been actually started and so that's all how it's saved and persisted. A great way to also look back on as a supervisor to see what plans were completed, what plans were not completed. So great for metrics and tracking. So I hope that answers that question.

Awesome. Thank you, Kevin. All right. I think we have one for Harish here. When we transfer AI chat to a human agent, does a case get created and get assigned to the technician? Does the case creation need to be set up by us? Or is that there by default?

Yes. So the way this works today is that you just use the current conversation setup. What happens when it gets transferred to a human agent is that it gets in queue for the human agent. They are still talking to the customers through the same conversational messaging session. A case is not created at this point. But they can choose to create a case if they want to right from there. So the current flow is that it goes to a human agent. They will continue the conversation as if it's a real-time conversation. But if it has to be a case creation, they can choose to create that case. There is a different thing for automatic case creation on the AI agent, where if a customer comes in, they start talking to the AI agent. And for whatever reason, they're like, I don't have time to talk to you right now. Can you just log a case and then get back to me later? They can still do that, in which case an automatic case creation will happen and the AI agent takes care of that.

Awesome. Thank you, Harish. Cool. We got one for Will here. How did data capture forms differ from the screen flows that are available in app today?

Yes, it's a great question. So the big difference is the level of dynamic behavior that you can have in data capture forms versus screen flows in that today. So both of these capabilities are entirely available offline, but within screen flow today a really complex data capture workflow might consist of 20, 30, sometimes 40 different screens, right, to navigate the user through, whereas data capture you can consolidate that down and make the experience a lot more dynamic. So depending on the answer to one question, it may expand the page and provide additional subsequent follow-up questions that become required, or if they answer in a different way, it may simplify the form. It may hide different aspects of the form that are no longer needed. So it really just makes the experience a lot more dynamic and efficient for the end user to be able to capture really complex data without the experience necessarily needing to be really complex.

Awesome. Thank you, Will. All right, let's see. Looking at these, we'll do one on Employee Service. Kevin, can you help us explain just like is Employee Service, is that part of Service Cloud? Is that included with Service Cloud? Or is it a separate SKU?

Yes. It's actually 3 new SKUs that we're launching with Employee Service. There's 1 SKU for the HR specialist and there's 2 SKUs for employees when they're logging into their employee portal hub. And so the 2 SKUs for the employees is based off of the frequency, of how often do they log in. So there are different rates for that and different SKUs. But overall, customers can buy a mix of the 2 employee SKUs depending on their needs. And if you have -- there's definitely some guides out there and some documentation around those new offerings, but that is a key difference, which is we're launching this as a new SKU, a couple of new SKUs actually. So definitely dive in a little bit there to learn more.

Cool. Thank you, Kevin. All righty here. For Will, for scheduling agent, what happens if an agent cannot find a slot that can work for the customer?

Yes. So similar to the Service Agent, this is highly configurable. So you can configure the agent to route the conversation to a real human if there's no slot available that the scheduling agent can find. This is what we call as sort of escalation to a human in this case. And that sort of works very similarly to how it works in the Service Agent. In this case, you would be going to a dispatcher, sort of a call center rep.

Awesome. Thank you, Will. Okay. We got one, Harish. We are just now working to migrate away from legacy chat with chatbot to the newer messaging, in-app and web. Do we need to have messaging, in-app and web, in place to begin working with Agentforce?

So you can start working with Agentforce right away, right? So -- but messaging in-app and web is one of the channels where you can deploy this agent. You can also deploy it on WhatsApp, on Facebook Messenger, SMS. Effectively, you are configuring the agent, you can test it on our Agentforce Builder. You can test exactly how it's working. But ultimately, when you want to expose it to your customers, you want it to be deployed on a channel. Messaging in-app and web is one of the channels. So if you have it up and running, you can expose this agent on your website, on your mobile app. For that, you will need that. But if you want to show this agent on some other platform like WhatsApp, you can certainly do that as well. So just think of it as one more channel required, but to actually get started with Agentforce, you don't have to. You can just sign up, start using it, test it extensively on the Agentforce Builder to see how it works. And then you start deploying it on the end channels.

Awesome. Thank you. And I think actually one more to you, Harish. Can you show the customer experience when the supervisor initiates the transfer to rep in the middle of the Agentforce conversation? Or I guess, what would that look like?

Okay. So when that happens, the message shows up to the customer that, okay, this conversation is now being transferred to a human agent because supervisor has decided to kind of intervene and then the customer gets connected to the human agent. So the customer doesn't have to do anything. They're still in the exact same UI, they have the exact same widget, same experience that they're getting. And they will be notified that they're now moving from the AI agent to a human agent. It's pretty seamless.

Awesome. And actually one more, I think this is back to you, Harish. Can we deploy Agentforce on legacy chat and skip the migration to messaging in-app and web?

No, you cannot. So legacy live chat, Agentforce is not supported on the legacy live chat. It's only supported on the new channels. So if messaging in-app and web is your chatbot experience on your website, you'll need that. It's not supported on live chat.

Awesome. Thank you. What else do we have here? We got a few minutes left. So we'll just try to do a couple more that come in. I guess, sorry, Harish to just overload you on questions here. But for real-time monitoring of agents, how is it determined like which agents are shown in that monitoring page?

So we can track up to 10 different agents, Agentforce agents, that will be monitored. All of those will show up, any of those 10 agents. Most customers don't have as many agents, but we can show all those agents. So you'll be able to configure which agents need to show up as well.

Awesome. Thank you. All right. So I know we have a few -- we didn't get to everyone's questions. What we will do is we'll follow up with you or your account managers will follow up and we'll make sure that you get the answers to those questions. Again, if you have anything specific that comes up maybe after this webinar, definitely reach out to your account managers. They can set up a meeting with you and explain more -- go into more detail about these features and innovations. Again, be on the lookout for all of that great release content and join the Serviceblazer community. We really appreciate the time today. And I think there is a form or a survey that will show up at the end of this, please let us know how we can make this better. We want to do this for you all so you can learn and really get excited about our upcoming releases. So any and all feedback is greatly appreciated. So I hope you all have a great rest of your day. And hey, we'll see you on the next release. All right. Bye all.