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

Hi. A very good morning to all of you who have joined. Thank you very much for joining today's session on the Key Takeaways from Dreamforce 2024 from a health care and life sciences perspective. Over the next 45 minutes, what we will be doing is we'll dive into the most important highlights, insights, innovations that emerged from this year's Dreamforce. And a quick introduction to the presenters for today. I'm Aswin Sundaresan. And I have along with me Ajay Arumugam. We are part of the Solution Engineering team of Salesforce for health care and life sciences, and we shall be delivering this session jointly today. Before we get started, a very quick look at the forward-looking statement. Salesforce is a publicly traded company. And we urge all our customers and prospects to make their buying decisions based on products and capability that are currently available. Right. All right. So at the outset, thank you, all of you, for taking time out of your busy schedules for attending this session. What I wanted to highlight was that whether you are looking to stay ahead of industry shifts or whether you're looking at implementing new strategies, I'm sure today's discussion is going to provide you and leave you with a lot of actionable insights in order to help you drive success in your respective organizations, right? With this, let's get started, yes. Yes, to quickly talk to you about Dreamforce. To many of you who may not be aware, Dreamforce is Salesforce's largest flagship event. And it is one of the biggest technology conferences in the world that brings together the entire Salesforce ecosystem together for learning, fun, community building, philanthropy and most important is for the innovation, right? And this year, we recently had this Dreamforce event in the mid of September and at our HQ in San Francisco. And we had Trailblazers from all over the world gathered to share their insights, successes and learn from the latest from industry innovations. So this year's Dreamforce, if I have to talk about the key highlights, we had over 45,000 people attending this event in person, with over 1 million joining online, right? We had over 1,500-plus sessions. And this was very well attended by 100-plus visionaries and AI experts across the globe. Now typically, from a health care and life sciences space, we had -- some of the highlights is what I wanted to quickly walk you through. We had the keynote which was primarily focused around how connected data and AI-powered solutions can improve outcomes and transform your interactions with patients, members, providers and partners. We also had customers like Kite Pharmaceuticals talk about the innovation and -- that they are doing on Salesforce and about the company's journey on the Salesforce platform. We had AccessHope, which is one of the leading cancer care providers, talking about the role of Salesforce in providing revolutionary cancer care, right? And we also had a lot of sessions from product management of Salesforce typically talking about the road map for some of our latest Health Cloud offerings across the Health Cloud and the Life Sciences Cloud; and a variety of engaging sessions cutting across innovations in the health care space, the future of med tech and pharma on the Life Sciences Cloud, just to name a few, right? So this is a snapshot of what we had from a HLS perspective, right? Now I just wanted to take a couple of minutes to talk about one of the key highlights of Dreamforce this year, which was the announcement and the launch of Agentforce, right? So Agentforce typically refers to a set of tools to create and customize agents across those Customer 360 offerings of Salesforce. And when we talk about Agentforce, these are autonomous agents. And these are proactive applications which are designed to execute very specialized tasks for an organization, which can really help improve productivity of employees and enhance the customer experience. These agents, in a nutshell, they leverage large language models in order to fully understand the context of the customer interactions and then reason through a variety of decisions to decide the next steps autonomously, right? So what really sets these agents apart is that they generate responses that are absolutely in line and consistent with your company's brand voice, right, and the guidelines that you have defined. And this leverages data, not only the Salesforce data, but also data which can be external to Salesforce, like data coming from the data cloud, data on your website, data on any other legacy applications that you may be having, right? And these agents typically operate 24/7 across a variety of channels like it can be your messaging channels, it can be your website, your community portals. And they operate within the guardrails as you specify, right? So what this typically means is that they know what kind of queries to engage for and which ones to stay away from, right? And when faced with complex issues that go beyond their scope, these agents can hand this off to a human expert, which can ensure that the queries are resolved in the most accurate and efficient manner, right? Now Salesforce also introduced these Agentforce agents and in a declarative framework. So what it typically means is that these agents can be set up with clicks and not code. And they can be set up in minutes. And they are absolutely scalable and they can work across any channel that your organization typically operates on, right? And to just extrapolate more on this Agentforce, we can take a quick look at some of the top use cases from an Agentforce perspective, right? So from a service perspective, these agents can replace your traditional chatbots that you may be having with AI-powered agents which can help you in handling a wide range of service requests, okay, without having the necessity for having any kind of preprogrammed scenario, thereby improving your customer service efficiency. In the case -- let me give an example. For example, in the case of a hospital or a provider, you can use these agents in order to automate processes like your appointment scheduling, or handling queries related to billing, or any kind of IP- and OP-related complaints or grievances, just to name a few. From a sales perspective, these sales agents can engage with your prospects 24/7. They can manage questions. They can answer questions, manage any kind of objections. And all this typically allows your sellers to focus on building deeper customer relationships, right? So this is something that can be available. From a provider perspective, this can be used for answering any kind of queries that may be coming from your international patients, right, round the clock. It can be 24/7. And similarly, from a med tech perspective, this can be of great use for managing any kind of objections that may be coming in from customers globally. This can also be used for providing the much-needed guidance or coaching to your sales reps in order to ensure that they are able to really articulate the value of their services very effectively, right? So it can act as both an assistive agent to your internal employees and it can act as an autonomous agent for your external stakeholders who may be wanting to reach out to your brand. Similarly, moving on, from a marketing perspective, these agents can be used to completely leverage AI for analyzing, generating, personalizing and optimizing your marketing campaigns based on your business goals. And this can be used for you to drive marketing campaigns either for driving awareness, conducting your CME events that you may be having at any given point in time. So all this can be -- can add a lot of value to the marketing efforts in your organizations. And from a commerce perspective, these agents can act as a digital concierge on your websites, which offers personalized product recommendations and assisting the users with various queries. And this can be very relevant when you're talking about an e-pharmacy kind of a setup, right? When you have people visiting your pharmacy, e-pharmacy site, you can have these agents give them prompt recommendations and what are the products they need to look at based on various things like the medical conditions, the past order history, the family details and so on and so forth, right? So these are all some of the areas where Agentforce can really add a lot of value to the health care and life sciences organizations in general, right? So what we wanted to do was we just wanted to dive a little deeper to give you a deeper look into the platform which delivers these experiences, right? So we can -- let's start, typically, from the bottom, where we talk about how we acquire data. Now for a health care organization, there is data that is spread across a wide range of applications. It includes the HIS; it can be the EMR solutions; it can be the laboratory information systems; the radiological information systems; the pharmacy systems; and so on, right. So we acquire. Using Salesforce, we can acquire all this data via a range of integration capabilities, okay? This typically ranges from your FHIRs and APIs to HL7 version 2 and message-based exchanges. And these can all be enabled by the prebuilt connectors that we have using our API-first MuleSoft technology, right? Now once we have all this data, what we do is we then harmonize and unify this data using Data Cloud in order to bring together everything that is applicable for a patient. When I say everything, it means a comprehensive view of the patient, which includes all the allergies that he has, the medical conditions that he is suffering from, details pertaining to the events or encounters with the hospital that he has had and so on. And this provides -- all this data goes a long way in providing a 360 view of the patient to your health care professionals, right? And then using this, we will activate the data in the downstream workflows, applications, analytics across the Customer 360 capabilities that we have. And on top of this, you can have Agentforce which can help in accomplishing, in automating various tasks that may need to be done. So to dive deeper into this. These agents that we are talking about can either be autonomous, that is they can complete the job that the customer has shown interest in. Or they can be assistive, wherein they can help your internal employees in order to complete that job as well, so it can either be autonomous or assistive. And this is an example of how trusted AI for health can be deployed in the flow of work, right? So just wanted to give you details on how this is delivered, and that's the intention behind taking you through this framework, right? Now moving on. From a health care perspective, we have a lot of participants on this call, you may be in different verticals of health care. You may be either in health care delivery or in health care financing, pharmaceuticals or medical technology. Whatever vertical you are in, Salesforce is here to help you embrace this new age safely and efficiently with our powerful purpose-built solutions, right? So just to give you more details. From a providers' perspective, Salesforce can help providers create those patient-centric experiences that drive better outcomes, okay? So it can help providers generate patient summaries which can tell a health care professional everything that is needed for him to know about the patient, okay, which includes allergies, the medications that he is on. And this summarization, in a few seconds, typically ensures that he is able to provide the much-needed support in a much faster way to the patients. And similarly, med tech companies can now drive commercial excellence and empower their sales teams using Salesforce. So Salesforce can help them with things like generation of sales call summaries, using which, they can find out what is the sentiment of the customers, what is it that they are showing interest in and so on. It can also help companies, in a conversation-like manner, find out what are the inventory levels across the supply chain that they cater to. And all this goes a long way in helping them become more efficient in their day-to-day operations, right? Now moving on. I'm sure you must be familiar with the Health Cloud that we launched a couple of years back. Now, when we talk about Health Cloud, Health Cloud is Salesforce's industry solution. It is tailor made for companies in the providers, payers, public health organization space. And the reason why we say it is tailor made for these companies is that it contains prebuilt data models which can help these companies go to market faster, right? And this application that we're talking about seamlessly amalgamates. It consolidates both your clinical and your nonclinical data, to give you that 360 view of the patient, which goes a long way in driving down inefficiencies and delivering insights in the flow of work, right? And a lot of companies have started using this and have started seeing a lot of benefits in this space. We have health agencies like -- which are global, like the Dallas Health and -- Services and Human Services, which leverage Health Cloud to protect the health and the well-being of over 2.6 million people today. And for this, they leverage Salesforce, right? And across this, what has been a constant with Salesforce is the innovation, right? And innovation is constantly being delivered over -- it's 3 times a year that you have the latest innovative features and capabilities that are being delivered to all our customers. And when we just want to talk about some of the recent innovations, when we talk about AI for health, some of the things that are available today will be getting instant generation of a summary of the patient, right? As I told you previously, the patient data can lie across a variety of system. Salesforce now makes it possible to provide a summary of the patient by consolidating all the data from various systems. And using large language models, it provides, it generates the summary so that anyone who is engaging with it knows very quickly in a few seconds everything about the patient and also knows what are the possible recommendations that can be given, right? Gen AI is also being leveraged in order to craft these patient-specific outreach e-mails, right? There may be so many patients who may be in different stages of their medical condition, right, in different demographics, belonging to different geographies and so on. And Salesforce can use generative AI in order to provide the specified and the personalized messaging to patients. Now, from a contact center perspective, there is innovation happening where we are talking about providing instant automated responses to queries, basis data that is available in various sources. It can be data which is grounded to the CRM, data available from other sources. So this automation of service replies to the customer queries goes a long way in deflecting the cases that typically lined up in your contact center, reducing the turnaround time and thereby driving a lot of efficiencies, right? And some of the impact that our customers have been -- begun seeing by virtue of these innovations would be an increase in patient volumes; increase in the member satisfaction; increase in patient referral volumes and so on; decrease in the time spent on providing manual updates, right? So these are some updates, basis the surveys that we do annually. These are the metrics and the impact that our customers have been able to witness, right? Moving on, I also wanted to take a couple of minutes to talk about the Life Sciences Cloud. So we announced the launch of our Life Sciences Cloud a couple of -- earlier this year, right? And Life Sciences Cloud, like Health Cloud, is a tailor-made solution for customers in the pharmaceutical space, for customers in the medical devices space. It contains prebuilt data models for these customers. And this solution helps customers accelerate their clinical development with integrated real-time health data. So this helps in connecting the patient and the providers like never before, enhancing the engagement between the patients and the providers and also enables the personalization and automation across people, processes and products, right? And there are a lot of AI-specific work that is happening in the Life Sciences Cloud as well. We have recently launched the Pharmacy Benefits Verification using generative AI. We've also launched how AI can be used for doing clinical trial participant auto-matching, okay, to find out who are the right candidates who can be enrolled in the clinical development programs. And this -- customers are beginning to see a lot of value with these innovations that are being rolled out to them, right. So now what we will do in the next couple of minutes is we will explore how Salesforce can enable providers to take your health care data from chaos to clarity by safely acquiring it from many of your systems, which includes your EHRs, your HISs and so on; and then harmonizing it in Data Cloud designed for health; and activating it within Salesforce, right? So we will take a quick look at a demo which walks us through the complete journey of the patient. And for doing this, I will request Ajay to take it over from here.

Sure. Thank you so much, Aswin. And I think you've set the context perfectly, right. So what we will do in the next section is essentially look at how these 3 aspects are going to play a part in unlocking not just AI but other insights and analytics across health and life sciences, right? So let's start with the first stage, which is acquisition, right? So acquisition of data. Now you want to acquire industry-specific data securely and accurately, right? So especially if you're looking at it from a provider perspective or a pharma perspective, you're going to be working with a lot of other solutions in the ecosystem, right, where clinical and nonclinical data is residing, for example, your HISs from a hospital standpoint. Or if you look at the pharma industry, you're going to be working with a lot of LIMS, RIMS or your traditional ERP systems or a quality management system, where a lot of these data is going to be scattered around people and process. And that's the acquisition part that we are really talking about, right? And we do that by using industry standards to accelerate any sort of an integration project, right? Now with Salesforce, we effortlessly integrate structured clinical data from any FHIR-compliant EMR with our prepackaged MuleSoft Direct integration, right? And we then utilize this industry standard, FHIR bulk data implementation guide to streamline any data ingestion into both Data Cloud or directly into Health Cloud, right? And we -- it's pretty much a very similar process when we really look at pharma, right, where we are working with a LIMS or RIMS system, where we need to bring that data into a Life Sciences Cloud or into a Data Cloud, we have those connectors available, right? Now we unlock valuable insights from all of these varied data sets using our prebuilt integrations to connect seamlessly into QHINs or any document repository storing any consolidated clinical data architecture files, right? So we are not really restricting ourselves to structured data available in these other systems. This data that we need for any analytics or AI or insights can be residing in unstructured documents as well. And with capabilities like a vector database, et cetera built into Data Cloud, we will be able to read these documents and make sense of them, right? So that's the first aspect of acquisition of data. Second is harmonizing or unifying this data, right? So harmonize your data for a holistic view of every patient or every customer or every persona that you'll want, right? Now how do we do that is we do that to -- the reason we do that is to achieve a true customer 360 or a patient 360 view, right? And that starts with our unified clinical data model, which is FHIR aligned, scoped at least to the USCDI and now available directly on Data Cloud, right? Now the data model in Data Cloud additionally includes things like care barriers of entities to capture any social determinants of health, empowering organizations to address and manage nonclinical factors that might influence a patient's outcome. And new with our October release, there's a robust adjudication claims data model as well. This is more from a payer's side of things. You now have access to full-fledged claims data model aligned with FHIR standards, capturing adjudicated claims data such as claims headers, line items, which includes procedures and medication. It also has adjudication details, payment information, diagnosis code, et cetera, right, which basically helps in supporting financial and clinical decision-making. In the future releases, there will also be terminology harmonization across different solutions and EMPI integration as well. Now that we have all of this data, right, we've acquired this data, we have harmonized that information to make sense of it or to create this Customer 360 or a patient 360, the next aspect is, of course, activating this, right? And we say -- when we say activate, we activate on your data in any downstream workflow or application and analytics. Now this could be related to AI or this could be just an automation that you're trying to run based on the information that is coming in, right? And it need not be any clinical data or any sort of ERP data, right? It could just be data which is streaming data coming in from a website and whatnot. Now that's what we are trying to activate and bring out insights, right? You can do that with actionable insights within Health Cloud or within the Life Sciences Cloud. So displaying a patient's score information and historical score trends in a very user-friendly interface. And also, in future, you will have instant access to any of this clinical data, right, for example, from an EMR, with our EMR fetch console in Health Cloud, for any -- for improved patient support. Now you will also be able to enable contextual decision-making by integrating insights from Health Cloud or Data Cloud directly into the provider's EMR workflow. Using the CDS hook service, clinicians can make informed decisions faster with more context. And in the future, you can activate real-time updates in any external system as well from data residing in Health Cloud using our FHIR subscriptions, which meet industry standards, right? Now that we've seen all this, let's look at this -- or probably I'll go through this a little bit more from an AI perspective, right? And now that we've acquired and harmonized this data, effectively curating or governing your data is so that you can activate your data to deliver on trusted AI, right, which is extremely important, especially from a HLS standpoint where you're working with sensitive information. It's important to have guardrails, especially when it comes to AI, to make sure that your data is not being misused. There is no corruption, or there is no data going, flowing outside of the system, so on and so forth, right? So the first up in our catalog of health-specific gen AI capabilities is assessment generation, right? Now this intends to be a huge time and manpower saver. Now this allows you to pull in PDF-based assessments; run through our generative engine; then populate into our assessment framework, differentiating questions from responses, easing the burden on collecting patient responses, let's say, to surveys and making that information actionable into care plans or identifying gaps in care or viewable in reports for deeper analysis. This is saving hours, if not days or weeks, depending on the volume of assessment in use. And the newest of our gen AI capabilities include the ability to, one, quickly generate a medical history, a medical summary or pre-call summaries on a patient for a care coordination with a single click. Now we also use Agentforce to summarize a complete provider profile for referral and patient analysis, the information about a provider, including his current and previous experience, his education, his accreditation, certification, licenses and languages that the provider speaks, right? Now there could also be trigger outreach and draft personalized content about a patient, to share with the patient or a payer provider. Now with that, let's jump into a quick demonstration. Now before that, let me just quickly set the context on what kind of journey we are going to see, right? So in our journey, we're going to be looking at a fictitious provider called Makana Health. And our patient persona is Charles. Now Charles is a high-risk patient and he's also a disengaged patient of Makana Health with multiple comorbidities, right? Now we'll look at how Salesforce can help Makana Health acquire patient health data; harmonize the profile for predictions, recommendations; and activate with digital agents to improve any patient experience, right? And we'll also look at it from 2 perspectives, not just from a patient's point of view but also from a care coordinator's point of view where our Salesforce agents are helping them deliver better patient experience. So we'll -- with that, let's jump into the demo. To start this journey, we'll begin in Data Cloud. So Data Cloud allows us to ingest and harmonize disparate data sources into a single metadata data model. Then we can map data attributes to a individual patient's profile. So let's take Charles for example. Data Cloud allows Makana Health to map his clinical claims and engagement data all to 1 unified Charles Green record. This allows Makana Health to get strategic and creative on how to best engage Charles to proactively better his health outcomes. Now one way of doing this is by creating segments. Segments allow Makana Health to personalize engagement messages and journeys to a cohort of patients. In this case, Makana Health has created a segment for patients with over 3 comorbidities, which also includes Charles. Now, within Data Cloud, we can specify the criteria for this segment, which means we can include and exclude data attributes and even incorporate calculated insights that measure a specific aspect of your patient like a unified health score or, in our case, a social health score. Now this allows Makana Health to hyperpersonalize patient outreach, increasing their chances of a patient like Charles engaging with the message. But for the -- but the personalization doesn't stop here. With Marketing Cloud, Makana Health can activate this segment and put these patients on a wellness education journey. With the goal of better patient outcomes in mind, branching logic will personalize a patient's experience based off their engagement activity. So when Charles receives the first email in this wellness education journey and he opens it, scrolls through the content, learns a thing or two about adjusting his diet and exercising safely, but ultimately he abandons it. But Makana Health has already accounted for this scenario and sends a notification to his dedicated care coordinator, who can then spring into action. The notification will bring the care coordinator directly to Charles Green's record within Health Cloud. Here, for example, let's say the care coordinator is Melinda. She can get a full 360 view into Charles by having visibility into, one, his high-level patient information and insights. She can also see all the engagement Charles has had with Makana through various channels. That could be through the mobile application, email, website, et cetera. She can also see all the relevant data that might be living in other data sources like claims or clinical encounters. And also, she finds recommendations and prediction based off of Charles's unified profile. But the world is getting needy and we like our information to come in fast and in a format which can be quickly consumed. So instead of searching to find this information, she can have an Agentforce assistant sift through all of this for her and tell her what is most important. Within seconds, she gets a summarized medical history full of key points, including recommendations and actions. In this case, Einstein is suggesting she invite Charles to an upcoming wellness seminar, due to his history of frequent ER visits because he has type 2 diabetes condition and because he recently opened that wellness best practices email that we saw earlier. So without even leaving Salesforce, the care coordinator can use the Agentforce assistant to draft and send a personalized email invite to Charles. That is taking proactive action to help better a patient's health outcome. Now let's switch back to Charles's view. He gets another notification. This time, it's an email from Melinda, who's his care coordinator. And the email says there is a nutrition seminar coming up in October and his care coordinator thinks it will be perfect for him. But he has a couple of questions maybe the virtual assistant will be able to answer him. Immediately, Charles can tell that this digital assistant is much more than a preprogrammed bot. In fact, Makana Health is leveraging the new Agentforce service agent that has been trained to handle nonclinical patient questions to help deflect trivial cases in their contact center. So let's take a view of this. Charles starts asking questions on the new -- on the upcoming health and nutrition seminar. And the Agentforce agent is able to respond to him with all the details, along with the link to join the seminar. But Charles further has a few questions on where is the clinic that it's being held in. So Agentforce is also able to answer that. And finally, Charles asks if there is any cost associated with the event. Or can he bring an additional guest? The agent is able to respond to this natural language free-flowing question. It is also saying that whenever there is a clinical question being asked, the Agentforce agent is saying that, "I will not be able to answer this. Can I reroute it to one of the specialists who can answer such a question?" And Charles goes ahead to attending -- or filling out the information to go ahead and attend the seminar. Now how is this different from any of the previous chatbots? Well, an Agentforce service agent is not created with an expansive dialogue tree to predict every single question. Instead, they are assigned topics. A topic could be general FAQ or even care plan task explanations, but these topics are the AI guardrails. They define the jobs your Agentforce service agent will or will not do. And the best part, topics are created with natural language descriptions rather than programming or code, taking a huge amount of manual up-front work and maintenance off of any admin's plate. So for example, this agent has been trained to answer any FAQs like we were seeing right now, but if Charles were to ask any clinical question, the Agentforce service agent will say it cannot answer and will redirect him to a live agent. Now companies who have incorporated Agentforce agents have already seen a case deflection rate of 40% to 50% in their call centers. And in Makana Health's case, we are seeing high-risk patient with multiple comorbidities take a step towards better health outcomes by signing up for a wellness seminar because without even talking to a person, Charles was able to, one, quickly get his questions answered; two, easily sign up for the seminar; and three, immediately get the confirmation; and began his journey towards living a healthier lifestyle. Now last but not the least, we come back to the power of the Salesforce platform. Activating data is much more than applying to it patient-focused scenarios, right? It just -- it's just as important to analyze trends to identify if our efforts are working or not working. At Makana Health, Tableau Pulse proactively monitors key metrics and notifies the care coordinator to help them connect the dots. So in our case, Melinda, who's our care coordinator, can see that her personalized engagement has led to lower readmission risks across the patient population, showing that truly knowing our patients does in fact lead to better care quality and improved health outcomes.

All right. Yes. Thank you. Thank you very much, Ajay, for the demo. And for all the participants, I believe this has given you a good overview into how Salesforce can help organizations leverage CRM, data and trusted AI to provide a differentiated experience not only to the internal stakeholders but also to the external stakeholders, right? With that, I just wanted to let you all know that you can always find out more details. If you want to tune into any of the sessions that you missed out in Dreamforce, you can find the recordings on our channel, which is Salesforce+, for these recordings. You can also go to Salesforce's Health Cloud or website in order to learn more and stay up-to-date on the latest innovations that are happening in this space, right. So at this point in time, we've come to the end of our session for today. Wanted to check if there are any questions, we would be happy to take a couple of questions.

Aswin, I think there's a question on the chat from [ Nishant ], "Are Salesforce Copilot and Agentforce different?" Right? So let me take that one. Now Agentforce is obviously autonomous agents. Now, we did have this concept of Salesforce Copilot from -- coming in from last year, but right now, Copilot has been rebranded into assistive agents, right? They still do a job of helping various personas within the organization with any sort of summarization or dedicated automation that is using gen AI in the background. Like we saw how for the -- from the demo, how we saw the care coordinator using the Einstein agent for help, Copilot also -- or assistive agents will also provide a similar support to any internal personas. With Agentforce agents, they are autonomous agents, which means that they are trained to do a specific job by defining what the job is, right? That could be in terms of the topics that they can support. That could be in the types of decisions that they're allowed to take in terms of automations, et cetera. And all of this is being done by purely drag-and-drop or a no-code way or declarative way of creating these agents, right? And that's the key difference between assistive agent versus a Agentforce agent. To summarize: Agentforce agents are completely autonomous, with guardrails put in place in terms of what they can do, whereas assistive agents can only do a specific functionality within a particular record or for a particular persona.

All right, yes. There are a couple of questions regarding -- related to Agentforce. People want to know where they can get more details pertaining to Agentforce. So I think one of the topmost resources that is available at your disposal is salesforce.com. You can visit the URL salesforce.com/agentforce, and you would be able to get everything that you need to know about Agentforce. There are some resources like demo videos. There are also trails that are available that can help you get up to speed with what is the application all about. So I would strongly urge all of you to visit this website, salesforce.com/agentforce, for learning more about it. Right. So I guess we are at the top of the hour. So we wanted to quickly thank all of you for your time and for attending this session. So thank you very much once again for your time.

Thanks, everyone.