Become an Agentforce Company | Salesforce

The two most powerful words in the world that we know are what if every great thing that I've ever been a part of began with those two words. And today, thousands of organizations are saying what if? With the power to act on those words like never before. What if every child had a tutor? What if every healthcare visit felt personal? What if every family had their own financial advisor? What if your business never had to sleep? What if. What if your company could solve problems before you even knew they existed? What if you could empower every employee with a limitless digital workforce that listens, learns and acts all day, every day? Well, this isn't some far fetched science fiction fantasy anymore. No, it's happening right now with AI from Salesforce. It's called agentforce. Agentforce turns your vision into reality. Think about it. A future where every student, patient, client, citizen, and customer experiences the best service possible. And your people, well, now they're free to focus on the work that matters most. All you have to do is bring your dreams. Imagine that.

What if.

What if every company was an agent force company?

What if?

Please welcome co founder Salesforce and Chief.

Technology officer Slack Parker Harris.

All right, welcome everyone. Welcome everyone here in the room. I think it's a full house. Look, we got people back there. There's an overflow. And thank you to everyone online. Where are the cameras? Right here and here. Welcome to World Tour, or Agent Forest. I guess I need to say Agent forest World Tour, D.C. i'm so excited to be back here. You know, I love D.C. i. I've been dedicated to the federal market, especially for Salesforce, for over. Well over a decade. And Dave, Ray, if you're here, correct me if it's even longer than that, but we've been working together here in D.C. to really drive a lot of change here and help make the federal government even more efficient and better to serve our citizens. But before we get the show started, we're going to do what we always do to thank each and every one of you. Each and every one of you who are our commercial customers, our federal customers, our SI partners? Nonprofits. If there are nonprofits in the room, give a shout out to all nonprofits. Raise your hand. Yeah. Thank you for being here. Thank you to all the stakeholders who are part of our community. For 26 years together, we have built something really, truly incredible. And we couldn't have done it without you. But as you know, 26 years ago, when I met Marc Benioff, we started the company on a core set of values. In 1999, you may not remember, but people didn't trust their credit card number on the Internet. They're like, I don't know if I'm gonna put my credit card number on the Internet, much less my customer list. They're like, no way. Trust was fundamental in 1999. It's still fundamental today. Today it's more about AI. We're not gonna use your data in our products. We are not gonna use your data to build models, give back to other customers. Your data is your data. It is not our product. That's everything about trust, customer success. I love innovation, but what's more important than innovation is customer success. With the technology that you have today, we want to make you successful. And if you're not successful, I hope you'll find in a Salesforce employee. Find me after the show. Tell us what's wrong. Tell us what we can do to make you more successful than, of course, innovations. Everything about today, you're going to see some incredible innovation. Agent, force, data, cloud. And of course, we believe a world based upon equality and sustainability. And with those values, we have created a company that has driven a lot of change, that we believe that business is the greatest platform for change. And what is that? Well, when I met Mark, he said, we're going to start a company with the 111 model. And I was like, Mark, what is the 111 model? I don't understand that. And he said, well, let me tell you, Parker, 1% of our equity, which was worth nothing at the time, we're going to put into a 501C3. It's pretty cool. Almost $800 million has been given away by Salesforce in all time. Giving to do good. But it's not just about money. It's fine to give money away. That is a very good thing. But it's also. And this is what we're going to talk about today, it's about human capital. And we put the human capital of Salesforce employees. They can give nine days off a year here in D.C. in Tokyo. I was just talking to Marc Benioff. He's off there somewhere in Japan, in San Francisco, Wherever we have a presence, our employees are giving back 9.6 million hours given back. And if you're a nonprofit in room, you know this. 60,000 or more than 60,000 companies are using our product for free or near free. You probably would like it entirely free. It's highly, highly discounted. Any money we make on that goes back into our nonprofit. It's always given back. We're not using that, that capital. We're only using it to keep that going. And also today I really want, I'm super excited. We are making a million dollar donation to American forests in the spirit of reforestation because we need more trees. Yeah, big shout out to that. So 26 years. We're doing well and doing good. We can do both at the same time. When I met Mark, he said we are not going to create this non profit and give back. Once we're successful. We're going to do it every step of the way. And that's the magic those values are baked in. And I believe it makes us a better company and it makes us. Look at that. 40.9 billion in projected revenue this year. That's incredible. But even better. World's most innovative companies. Top 100 companies that care in philanthropy. World's most ethical companies. Those are all shared values. That's doing well and doing good all together. And as we're doing well and doing good, it's about serving all stakeholders. And here in D.C. i'm especially reminded of the stakeholders of state and local governments. I'm right now dedicating myself in San Francisco to do a lot of work locally in the San Francisco market with our new mayor to improve the state of San Francisco. And we're going to do that with Agentforth with Data Cloud, with everything we're talking about today. But also 50 states, not just San Francisco, 100 federal federal agencies, 60,000 nonprofits that we just talked about. There's a lot of those organizations, Boys and Girls Clubs. You're going to hear a lot more about that organization later with a great video, a great story, but I want to bring it home here into the room. I want to tell you a little story about the United States Army. I'd like to welcome Bob o'. Brien. Let's get Bob up here.

Bob?

Oh yeah. I keep thinking there's some slide coming up. Bob. I got all confused. All right. We're supposed to stand here so that people can see our beautiful logo and we could look at the cameras. So Bob, welcome. Now you, you. Thank you for your service by the way. You certain? Yeah. So Bob, I don't think everyone knows who you are and what you're doing, but it's around human capital in the US army, maybe tell everyone what mission you're on right now.

Okay, thanks.

Parker, is that on in here? Let's see. Technical support.

Hello.

We need some help here. There we go. Sorry about that, Bob.

Thanks.

We got a whole army of people to help you There we go.

Thanks.

So I'm Bob O'. Brien. I'm a 32 year veteran of the United States army and I've been hired back after retiring last summer to continue leading a program called the US Army Command Assessment Program. We're the largest leader assessment program in the world. And every year we bring in over 2000 candidates to assess them over a four day period and make a selection for putting them in command and key leader positions.

Yeah, and we were talking a little bit backstage before we got up here. A lot of data points you're tracking. You know, it's not just what other leaders are reporting, but there's some psychometric data when you think about data. And also like we're going to talk about AI, the potential maybe of AI, how that might help you, maybe talk a little bit about where you see this going and any advice you have for the audience.

Sure. So across these 2,000 candidates, and we've been assessing them for over five years now, so we've got 9,000 candidates that have come through our assessment program. We gather over 3,000 data points on each of these candidates and using a series of psychometric assessments, personality assessments, intelligence tests, behavioral tests, and then we do on site work samples. And we expand what has been prior to five years ago, a selection process that considered every individual for about two minutes. And we've expanded that to 17 and a half contact hours with the candidates. So we now have over 27 million data points on key leader behaviors. And we're gathering that in a clean manner, which is a great first step for us. We've taken what used to be a very dirty data pool and we've cleaned that data pool as we've gathered it, and we're making selections on whether somebody should be certified, qualified to do a job, or not yet certified, disqualified for a period of time to do a job. And as we do that, about 13% of our people are not yet certified. And we have a large leader development program that's tailored to the individual. We use data to help develop the leaders and prepare them to come back and be successful. We've got a number of cases where leaders have come and been unsuccessful one time and come back and been very successful. Those leaders that get certified, once they do, we're able to take the data and not only use that for the selection process, but we can use that data to deliberately build teams of people using the data. And we just finished our slaving process and briefed the chief of staff of the army this week. And we've had some cases where we have deliberately recommended against partnership teams coming together because we had leaders who had the exact same personality and behavior makeup, and we broke them apart even though they were certified because the same stimulus would cause them to act the same way.

Yeah. Someone once told me, we did an analysis that I'm the complete opposite of my wife and that's why it works. That's right. So, anyway, Bob, thank you for that story. Thank you for your partnership. We'd love to help you more. Thank you for being here.

Thanks. Appreciate it.

Yeah. Well, you know, I love that story, Bob, because the one point you made of, like, not everyone makes it the first time, but you're investing in them and you're bringing them back. And it's about that human capital. It's not about, like, getting rid of employees. It's not about, you know, rejecting them if they don't pass some test. It's about investing in them. And this is a great example that customer success is driven by human capital. It's driven by human beings, that if you invest in those humans, the frontline workers or the engaged employees, you will have more successful customer interactions or citizen interactions. Well, that's great, but everyone's overwhelmed. You know, here in D.C. we're having a lot of talk around efficiency, which is wonderful. And that means potentially less people in some organizations. And the people that are there are worried. They're like, whoa, how are we going to get our work done? There's a talent gap. Do we have all the talent we need? There's a fixed capacity. I wish I could hire as many engineers as I could to give you all of this innovation even faster, but I can't. Productivity is stalled, burnout. These are all issues you're all seeing in your organizations and in your government agencies. Well, guess what? People don't care. People don't care that your talent is not all there, that you have people that are burned out. You have less people. The customers want more. The citizens want more. They expect you to know who they are. They expect zero hold time. And they say, I'm frustrated with some problem. And they want to. When you answer the phone or you answer their text or their chat or however you're interacting with them, you better know them and you better be an expert to them. I hate when I call some customer service line and they're like, the first answer is like, no, you don't understand. Please put me with someone who actually can help me. We've all had that, but we don't like that. And we want More so workforces are overwhelmed, customers want more. That is the problem that we all see today. But what if workforce had no limits? What if there were no limits? And it's not about no limits. And like we're gonna all hire and create all these incredible employees. It's about humans and AI working together. And that's what we are doing with Agentforce. That's what we have been building, we've been taking, we took 26 years of IP. You all know all of our clouds. We started with Salesforce Automation, we added service, we bought Market automation, bought E Commerce. But we've rebuilt all those applications. It's now one deeply unified platform of Customer360 applications. We built, thank thankfully we built that integrated data cloud because data is the lifeblood of AI. It's the lifeblood of personalized customer interactions. It all works on that unified Salesforce platform. You don't have to learn multiple platforms. You don't have to be an expert programmer. You know, Salesforce, we make it easy. You can use that platform powered by data cloud through all those touch points to give agentic experiences and basically digital employees to your workforce so that you can scale infinitely, that it'll be trusted, easy to deploy. The humans are right there working with the AI. We're not getting rid of the humans and you can solve that. Zero hold time. And it's also completely open. We're not this closed platform. So we know that we have to fit into your architecture. You know, agent force is powering this digital labor revolution. You think about hiring employees, that's important. I think about it. I think about like Bob, making those employees better leaders, better at the skills that they need to be successful. But you're also going to start hiring digital employees which is kind of this weird idea. You may actually fire digital employees, which is a really weird idea. You might have. Maybe there's an agent, you know, not, not doing such a good job. Okay, well, sorry you didn't make the cut but you're going to start thinking about the legal agents, the financial, the financial agents, the developer agents, the customer service agents. These are experts in your organization that you're going to train and you're going to know them better than I will. I can't give you, you know your business better than we do. So those humans and all the ip, you're going to imbue that into this agentic platform to create these digital employees, these digital agents. Salesforce is doing just that. You know, we were, we've been going as fast as we can. I Think you saw the pace of innovation from Salesforce, from everyone in the market. We're going as fast as we can, but it's because it's a race. It's a race right now to take the power of like, we're all shocked by the power of these LLMs. The power power of AI has really hit that tipping point in the past two years. We have to go as fast as possible. But we're all a little scared. Salesforce was a little scared. We're like, I don't know if we're quite ready to put agent force on our website to help all our customers because hey, might. There might be a few problems with it. It may not quite work. Mark said, nope, you're doing it right now. You're putting it on. We're like, okay. And you know. And it didn't work perfectly at first. There were a few issues, but we went for it. We put it out there and we made it better. Each hour, every time there's an interaction because we have this platform, we know what's going on. We know if there's a problem. If a customer didn't have the right answer, we can debug it. We'll talk about that later. We have a full platform. It's not just a little LLM. And with that, we've driven 30,000 conversations a week. Our agents are talking to our customers and they are solving those problems. 85% of the time, customers just, they're happy. You solved my problem.

Great.

Awesome. 15% of the time those are more complex problems. And so we had a human come in to have that higher value interaction to really help the customers. And it was humans and AI together solving and scaling that. Scaling Salesforce because we can't hire enough people to support you. We're also doing that in sales. 25,000 sellers have a dedicated sales coach. It's like if you could hire the best sales coach and put them side by side, every employee that's selling wouldn't you want to do that? But you can't hire enough people to do that. But now you can put the sales coach, that's an agent. And the best thing about it is the salespeople aren't embarrassed to ask questions of that sales coach because it's not a human being. So it's this weird thing that they're happy to get that help. 3.5 thousand exec briefs generated by agentforce. So that's what we're doing at Salesforce in our customer base. RBC wealth management has an issue where they want to make sure that their wealth advisors are serving their clients the best way possible. And how do they scale that? Well, they scale that with an agent side by side with that wealth manager because that's a highly personalized interaction. Even better and more powerful with the power of data cloud powering agent force for those wealth advisors. Remarkable. How many of you know about remarkable? It's these amazing tablets. It's basically like paper. So it's not paper. Incredible. But you may like, okay, I need a little help. How do I. You know, there's gestures in it. Like I need to have the text be recognized online and turn it. You know, the. My writing turned into text because I want to save it, I want to use it. So how do I do that? Or a problem with my account. They couldn't scale the support enough, fast enough. So they put agent for us right in the middle of remarkable support. And now it's deflecting 35,000 inquiries, inquiries. Solving the problems faster. That's what we want. Faster and better. So the customers are happier. All right, well, we're going to show you how you can do that in your companies, how you can do it as a nonprofit, as a commercial enterprise, as a government contractor, as a government agency. We're going to show you how to do that, how to do that across the customer. 360, all those touch points, how to make it more personalized with data cloud. This data is the lifeblood, as I've said, of this personalized interactions and the power of AI and most importantly, this future of AI. How are you going to go quickly in this world of AI? We're going to do that with Agent Force. And to tell you more about that and show you some incredible demos, I want to invite Avanika Ramesh. I just mispronounced your name. Avantika. Avantika. Apologies, Avantika. Did I get it right?

You got it right. Thank you.

Sorry about that. Avantika. Avantika Ramash, Senior director of Product management. Take it away.

Thanks, Parker. Good morning, D.C. so glad to be here right at the cusp of cherry blossom season. And if you think these cherry blossoms are blooming fast, well, Agent Force is moving faster. Agentforce is a massive transformation, not just for us at Salesforce, but also for every single one of your businesses.

Agents.

You know, this transformation we're seeing today reminds me of a revolution that we saw 50 years ago with the advent of the CPU, the central processing unit. For the first time, we had a system that could process inputs and perform computations. But what good was a CPU on its own, it needed peripherals, it needed an operating system, it needed memory, needed all this scaffolding around the cpu, which is what made it usable as a computer and led to its mass adoption. And now here we are today with a new revolution of large language models, LLMs. For the first time, we have systems that can understand, reason and respond with natural human language. But just like a cpu, how good is an LLM on its own? We need to build on top of these large language models in order to unlock their full potential. And it starts with data. Good AI needs good data. And we need to feed your organizational data in real time to these models. But how do we do that? These LLMs are trained on a finite set of data at a set moment in time. So the magic is in the prompts. The prompts that you send to these models need to be grounded. They can be grounded in your structured and unstructured data, your metadata, even the underlying semantics of your data. And with good prompts, you get relevant responses, but you also want to surface these responses in relevant interfaces. That's where the application layer comes in. We want to make sure that your AI is context aware and well integrated into your workflows and applications. But we know that AI can go beyond simply generating responses, it can even take actions. And that's where AI agents come into the picture. Agents can reason on top of your data, on top of your applications, in order to take actions across your business workflows. Now, as you can see here, this is a lot to bring together in order to make LLMs usable. That's why we've done a lot of the heavy lifting for you, so you don't have to make those investments. And brought all these layers and services into one deeply trusted and unified platform platform to make AI usable for your enterprise. We've also designed this platform so that it's as open as possible, allowing you to connect to your own large language models, allowing you to connect into your own systems and APIs, even access your data all around the world. This is that single trinity of data apps and agents. And we call this platform AgentForce, the digital labor platform. We built this agentic layer on top of your data and your applications to help you build these agents quickly and realize value 16 times faster, with 75% more accurate and relevant responses. Now, we've designed AgentForce to be well integrated into your business. Look at all those zero copy data partnerships. This allows you to connect and access your data regardless of where it is in the world. Then we have these AI partnerships. We Allow you to access a whole host of large language models across vendors or even connect your own models. And with our new strategic partnership with Google, we're bringing Gemini, Vertex and Google Cloud straight into agentforce. Now, something new you might have noticed here is our Agent Exchange. We have over 200 partners who are actively building agent templates and pre built actions for you to help you deploy these agents a lot faster. And what you're seeing here IS system for AI applications in the world. Now speaking of actions, AgentForce can take actions both within Salesforce and outside of Salesforce. It can qualify leads, can schedule appointments, or even update inventory on your behalf. On top of that, it can even take action side of Salesforce. For example, it can process a refund in SAP or onboard a new employee in workday. So now that you've learned about the platform and the ecosystem, what about these agents themselves? Well, first it starts with some sort of trigger. This trigger could either be some sort of anomaly in your data, a change in customer behavior, or even human input. Then we have the reasoning engine that powers agentforce that's able to assess the context, gather more data on demand and generate a plan of action. Now this plan could be as simple as generating a single shot response or as complex as orchestrating actions across multiple systems. And finally, we have our outcomes. Are agents able to orchestrate these actions in order to complete an entire business workflow? As we can see here? Now, as we look at AgentForce and all the capabilities, one thing I love to see is how this comes to life. My team has been hard at work building all these innovations and it's gratifying when our customers can put these innovations to use and innovate for their companies. I've had the pleasure of working with wonderful customers like Fisher and Paykel, an AgentForce company. Fisher and Paykel is known for their high quality products and and premium services and craftsmanship. Now, as their business grew, it was equally important for their customer service to scale and be just as premium as their products. And that's why they turned to AgentForce, so they could deliver these exceptional customer service experiences at scale. Now, before we get into what Fisher and Paykel has done, I have a quick side story to share. Last month I was going through a renovation in my kitchen. And for anyone going through remodeling, you want to make sure you measure twice and order once, not the other way around like I did because of course I ended up with the wrong size refrigerator. Now the movers were in the room and I was panicking. I was trying to get a hold of my refrigerator company and literally get on call with the agent. Now, I'm sure you all have been in similar experiences, so let me actually show you what that experience was like for me. So I'm going to go ahead and call customer service. Hello and thank you for calling customer service.

If you know the extension of the.

Party you are trying to reach, you.

May dial it at any time.

To hear our store hours, please press 1 to start a return.

Please.

All right, that's enough. I'm sure you all can relate, right? And especially when I'm in panic mode just trying to get a hold of an agent, this kind of experience is just not helpful. In fact, there is a term in the service world for this type of experience, and it's called deflection, which is essentially deflecting the human inquiry away from a human agent. But of course, the customer doesn't get the help that they need. Well, the good news is customer service doesn't have to remain this way because we have customers and businesses like Fisher and Paykel who are at the cutting edge and ready to transform this experience for their customers. So now let's actually see what my experience could have been like if I had instead bought my refrigerator from Fisher and Paykel.

Hi, I'm Will, your Fisher and Paykel AI assistant. How can I help you today?

Hi Will, it's Avantika. So I had accidentally ordered the wrong size refrigerator. I'm afraid it's a little small, so is there any way I can get a replacement?

That sounds frustrating, but I'm here to help. Is this about the 17.1 cubic foot Series 7 refrigerator you purchased on March 3rd?

Yes, that's correct.

I have a couple larger capacity models in mind that offer the same benefits as your current fridge. Are you able to take a picture of the space so I can recommend the best option?

Yeah, I have a picture on hand. How do I get it over to you?

Great. I've just sent you a text message where you can upload a photo.

Perfect. Got your text. Let me go ahead and select my picture and just send it over to you.

Thank you, Avantika. Based on the dimensions of the space, I recommend the 20.1 cubic foot Series 7 refrigerator. It offers plenty of flexible space for cold and frozen food storage. Would you like to go with this option?

I like what I'm seeing. How soon can you get delivered, though?

Great. The soonest delivery appointment available is March 21 from 12pm to 6pm does that work?

Yes, Friday works for me, but I do Have a dinner around five. Is there any way that you could get it delivered between 12 to 3pm instead?

Unfortunately, I'm not able to reschedule to other times. If you would like, I can connect you with a representative to explore other options.

You know what, that's fine. I'll get back to you, Will. Thank you. All right, right off the bat, I'm sure we can all agree that that experience was was completely different and better. First of all, Will knew who I was. He was able to look at my order, process a replacement for me. But of course it could have been better because Will didn't have the ability to reschedule my delivery. Well, we have to stress Will didn't have a capability agent. So what we're going to do together is actually go into AgentForce and see give Will this new capability within our platform. So let's do this together. We're going to go into Agent Builder. This is where all the magic happens. What you see here is our agent Will. We start by seeing a description of Will's capabilities. He's an AI powered agent for Fisher and Paykel and we also see his role. Then we can also see all the channels he's activated on like Apple messages, email, Facebook messenger, even voice. Let's get into the topics are skills or jobs to be done that Will is capable of. As you can see here, he can answer customer FAQs, he can answer general questions and manage orders and even answer to product inquiries. But as you can see here, he doesn't have the ability to to reschedule orders and delivery timelines. So we're going to go ahead and design this new topic for him. So let's go ahead and hit new and describe the topic. Now all I need to do here is describe what new ability I want to give Will in natural language. Now I'm not going to do all the typing in the audience so I have it pasted right here. We want Will to manage product deliveries and inventory. Now once I hit next, you'll notice that AgentForest does a lot of the hard work for me. It's able to craft that into a topic, describe it so that the reasoning engine knows when to invoke this topic. And it's also able to describe the scope, these are the guardrails of what it should and shouldn't be doing. And finally we have instructions, more specifics around the brand voice and tone and interaction. So now that we have all these details here, again all described in natural language, we're going to go ahead and Start prescribing actions within this topic. Now what you'll see here, it's recommended some out of the box actions that are most suitable for this topic. But on top of that it's also looked at my existing investments in the platform, my flows, my prompt templates, any APIs I have, and it's able to craft them into actions for my agent as we can see here. So went ahead and selected those for me. I like what I'm seeing. Let's go ahead and create this new topic. So you see that new topic added right there. Let's quickly review all the details. The configuration looks good. We have our actions. Let's review that. Now for the fun part, we get to test it live. So remember I was asking Will to reschedule my delivery. So let's actually see. Will is capable of doing that. So I'm going to type in my name and see if Will can deliver my new refrigerator between 12 to 3pm it's about the 20.1 refrigerator and as Will is thinking through my question, what you see here in the middle is reasoning engine at work. You get full transparency into how your agent is reasoning, how it's classifying these utterances into the right topics and orchestrating the right set of actions. And there we go. Will is able to reschedule my delivery and on top of that I can see how he went through and navigated all these actions in order to come up with his final results. I can even provide feedback to my agent, so I have data to continue refining and improving it over time. So now that we tested this within Agent Builder, why don't we give Will a call one more time and actually prove it out to you?

Hi, I'm Will, your Fisher and Paykel AI assistant. How can I help you today?

Hi Will, it's Avantika again. I wanted to see if it is still possible to reschedule my delivery to Friday between 12 to 3pm.

Is this about the 20.1 cubic foot Series 7 refrigerator?

Yes, that's right.

I was able to move a few things around and secured a slot for your fridge delivery. Derek J will be there between 12pm and 3pm on March 21. Is there anything else I can help you with?

That's perfect. Thank you so much Will. There you go. Within a few minutes. It was that simple. I wrote no lines of and I was able to give our agent Will this new capability to manage orders and reschedule deliveries. And if I can do this without writing any code, trust me, you all can too. So I Hope you can join my team out on the campground after this keynote to get hands on and see this magic for yourselves. Thank you all so much for following along. Now I'm going to hand it back to Parker.

All right, Avantika, great job. That was awesome. And I love the demonstration. I love the demonstration with Voice too. It's really, really powerful. You just saw a great story of how to build with AgentForce. Unfortunately, Avantika didn't have enough time to demonstrate everything we have in the platform. We actually just had our conference, as I mentioned earlier, our developer conference. So you saw like, how is the reasoning happening? We saw that in that demonstration, but there's so much more. One of the things that I love that we just came out with is the Developer Edition. So all of you can now actually do Agent Forest and Data Cloud for free and learn it in a in Developer Edition. Also, how am I going to develop this and how am I going to debug it? How am I going to test it? We have a testing center, we have a debugger, we have a cli. It's a full, full platform. That's what we mean by it's not just the LLM. It is a full platform. A lot to see. I'm sure you can see more of it on the Expo later, but we're not going to let you go yet because we want to talk about how does data power AI and how are you going to unlock all of that trapped data in your enterprise? And to really, really tell you all about that, please bring up Marianne Patel, SVP of Product Management. Welcome, Marianne.

Thank you, Parker, Leading product for Sales Cloud. Talking to you is the favorite part of my job. And a question that I often hear is, hey, do I have to train an LLM on my organization's data? And honestly, thankfully, the answer is no. This is really hard for most of us. It is really expensive, it's not scalable, and frankly, a lot of people don't have the resources to do that. But that's why I'm thankful for Parker because we have been making the hard things easy for the last 26 years and we continue to do that with the prompt. The prompt, like Avantika just showed you, is simple conversational instructions and utterances, and that is how you get value out of the LLM. Even better, we have added retrieval augmented generation, which is a fancy way of saying we retrieve the information, structured and unstructured, from all of your data sources, we augment the prompt with your data, we bring your data to the LLM and that's how you unlock the value and then we generate the trusted, accurate response that you need to deliver that amazing personalized experience. This is the power of Data Cloud. But I know you're all thinking, ooh, there's probably some data that AI needs that I don't have access to yet. And that is what we see with a lot of customers. A lot of your data is siloed. It's locked. Locked data is unfortunately locked value. But that is why we have built Data Cloud. We are incredibly excited about this because this is your hyperscale engine inside of Salesforce. We allow you to bring all of your data lakes, your ERP spreadsheets, whatever it may be. You can pull it all into Data Cloud. We have hundreds of connectors to make it easy for you, for you to connect that in and then you're bringing that into AgentForce. Data cloud is the foundation for AgentForce and it's incredibly important. But I know the one thing that is on everyone's mind in this room, which is, hey, my data is sensitive. Just like Parker said, your data is my data. I want to make sure that I protect it. And that is why we've built robust governance and data security right into Data Cloud so you can feel safe that your data is there and trusted. The way that we do this is with AgentForce and Atlas. So if you think about that reasoning engine that Avantika was showing you in the middle, this is what that looks like. It looks pretty complicated, maybe intentionally complicated, but I'm going to make it easy for you. In the upper right, that's Data Cloud. That's where you bring in all of your structured, unstructured data. It's pretty easy. If we start on the left, you ask a question, you gave it some instructions and then we're pulling it into the planner. Let's think what a human does. When you ask me a question first I think, what's the contextually relevant data that I need? And to answer the question and then I create a plan and I think about what are the steps that I need to do. And I'll go through that a couple times and make sure that I'm iterating through so that we get the right outcome. That's exactly what AgentForce is doing. It's pulling all of that into the planner. It's using Data Cloud and it is unlocking the value in your data with AI. Vivint is an agent force company. They are a home security and Automation company that provides 24. 7 customer service and proactive monitoring and installation they deeply care about scaling their business and providing service and that is why they use AgentForce. The best thing is they are not starting from scratch. They have invested in their processes, their business, their data. It's all inside of Salesforce. For them to use AI, it just takes a couple of steps. So now to show you a live demo. I'm going to welcome Miles and Lynn to this stage and they are going to show you how AgentForce helps make customer service as proactive as possible. So first we're going to start in the Vivint app right here. This is an AI that you all probably feel comfortable using. You ask yet a question? But what's great is that it Agent Force has data cloud. Behind the scenes, it knows Vivint's business. Trusted knowledge, articles, troubleshooting, product specs, it's all there. So when I ask a question, it knows what to do. But let's be honest, who here has time to go to a site, ask a question? This is a home security company. I care about my family. I want them to tell me that something's wrong with my system first. So let's see how AgentForce becomes proactive. It starts with data. So we're going to go right into data cloud and we are going to create a new data stream. Vivint keeps their telemetry data inside of Snowflake and I'm sure you all keep your data in other places. So we're going to go in and create a data stream and at the top you'll see all that Salesforce data right there. Super easy to connect in. And as we scroll in, our 200 plus data connectors are right there for you. And with one click, I can select Snowflake and make some configurations. Behind the scenes, again, we've made the hard things easy. And in the background what we're doing is we are taking that telemetry data out of Snowflake, we're harmonizing it, we're doing identity resolution and then we get this beautiful visualization behind the scenes. At least I think it's beautiful because I'm an engineer and I'm a nerd. But what you will see here is you have telemetry data that this is now connected into data cloud. But what's more, it's also connected to the customer. So all of that information is right there. How do we make sure that it's safe and secure? Trust is our number one value. And so we have built robust data governance and compliance right in. We are so excited that we're also using AI here to make your job way easier. When you pull in all of this data, AI classification helps you say, is this telemetry data? Maybe there's CCPA implications, gdpr, hipaa, all of us want to make sure that our data is protected. And so once the tagging is there, you can of course edit it, but when you're ready, you can create a policy. So with just a couple of clicks, what I'm doing is I'm determining when do I apply data masking, who has access to this information. But the power with the platform is that you build it once and it is available everywhere. So then this policy is applied when you're testing, when you're in your call center, on your website, or it even helps you decide whether your legal team has access to information or an analyst. You build it once, you set it and you forget it. And that's how you bring humans and AI together. Okay, so we have our policy in place. Now let's go and try and test this. If you look up here again, complicated screen. Why? Because Vivint has a lot of different products and they have to think about for every piece of telemetry data, what they would do in terms of when a sensor is giving an error signal. What do I check next? So how might they use agentforce to make this proactive? You bring agents in, of course, and it becomes nice and simple, almost too simple, because you have that amazing reasoning engine of Atlas that I was just showing you. I'm here giving it information about the customer, their telemetry data, their device and agent force can do that. Agentic reasoning. Is this the first time that I'm seeing this issue? Have they seen it again? What device are they using? Does it have the latest firmware? All of that information is here. I don't need to code it because I know no one in this room wants to keep all of those flows maintained. That's not sustainable either. You want to really drive growth. Okay, so now that we have it there, Miles, can you trigger this flow so we can show everyone what agentic reasoning looks like? Awesome. So what we're going to see is I have a device. It's sort of at that tipping point where something's wrong. He's going to issue that debugging flow or applying all of that governance behind the scenes. And if you look at my mobile application, you'll see there's now an alert because what we are seeing is that something is wrong in this system and Vivint is able to provide proactive service in the Middle you can see, ooh, it looks like the WI fi is dropping. There's potential issues. And AgentForce knows that I have a customer care package. And so it's also recommending a technician to come to my house, which is awesome. This is so proactive. And then what I love best is all of that telemetry data, all of that diagnostics that I just showed you. When the technician comes to my house, they're also able to get access to all of that information and governance. So they have all the tools they need to get started. And that is how Vivint or any of your companies can bring proactive service into AgentForce with us. So come on that journey with us. We're so excited for you. And back to you, Parker.

All right, give a big hand to Maryam. Great job, Maryam.

All right.

You saw how to build agents with the agent force. You saw the power of bringing data and unlocking all that trapped data to power those agents. But now to bring it all home because it's also important is how is that data and are those agents? How is it helping you with all those customer touch points across the customer360? And to tell you more about that, please welcome John Moore, director of Product marketing here in Washington, D.C. welcome.

Thank you, Parker. It's good to see you all. DC I love looking out in the audience and seeing some familiar faces. But I recognize while some of you may be familiar with salesforce, some of you may be just getting introduced. So I want to share with you a really grounding statement about our mission. So we're all starting from the same page. Since the beginning, it's been our mission to help you to create new connections with your customers, connect with your customers in whole new ways. We've done that by helping you to build a customer360 which connects every part of your business across the entire enterprise, all integrated on our deeply unified platform. And now AgentForce has been extended into every single one of those experiences. So this is exciting because we didn't even have this language in our lexicon this time last year, for the first time, we're landing with agents in D.C. and now every application has been agentified. And I'll be able to show you how by just walking you through the platform. So starting with sales cloud, agentforce for sales allows you to offload a lot of those tedious, repetitive tasks to agents, freeing up your team to be able to focus on high impact work that really drives the business forward. Now I realize I'm starting with an example that may not land initially with everybody in the room. Because you're not in the business of direct selling nonprofit government education. I'm looking at you. You have a home here as well. Because fortunately, as the world's number one AICRM relationship is literally our middle name. And relationships sit at the heart of sales cloud and your business. And those valuable constituent relationships, customer relationships, student relationships that you own are fed and cultivated by transformative experiences that agent force for service helps you to create. With agents in service, you've got humans and agents together delivering proactive service with a personalized touch. And that helps customers like Heathrow see a great reduction in their call handle rate. And how you reach those customers and stakeholders is with marketing cloud. This is your engagement engine. This is how you are able to keep everybody involved on the journey. And agents help you to launch highly customized campaigns, targeted campaigns that save you a lot of time, time that we just don't seem to have. Especially if you're in a fast paced, highly transactional environment like commerce. Commerce Cloud agents give you assistance on the buyer front. You've got buyer agents helping your buyers with reordering personal shopping agents, which I could certainly put to good use, helping your customers find the right products at the right times, automatically adding products to their carts. And as you already saw in Avantika's demo, Fisher and Paykel is using an AI agent wheel to help them cut down on the time they're using, spending time working out orders. And speaking of orders, with an agentified revenue and orders, you can automate the entire revenue life cycle from quoting to contracting to billing. And as you heard from Marianne, all of this is powered by your data. Now, Tableau allows you to be able to view, interact and understand that data in new ways. Imagine being able to access AI powered insights inside of every application. That's exactly what Box is doing. They're unlocking powerful insights and AI generated visualizations and 97% faster. I mean, think about the time and effort saved multiplied across your entire enterprise. Speaking of time and effort saved, this is one of my favorites because I live it every day. I've said it before, I'll say it again. If you're serious about productivity, you have to be serious about Slack. Slack is a productivity platform that I use and everyone here can use to bring together all of your people, all your data, all your knowledge, all your applications in one place so you can collaborate in real time, in the flow of work. And thanks to mulesoft, out of the box connectors and low code tools, now your agents can Take action everywhere, including in third party and legacy systems. Now, all this has happened over the course of like the last six months. We launched all this at Dreamforce and we've had to move so fast, as Parker stated, because of all the change that's happened around us. Think about how much change has happened in your industries in the past six months. Forget months, Weeks in the past six weeks. And I'm off script now. And production's probably having a meltdown. I promise I'm sticking to the time. But I do feel compelled to say this because in the past several weeks and months, we've seen so much change in our city, in our nation. It is not an exaggeration to say that in the last six weeks, we've seen significant change in the world. And navigating transformation during that type of change, that has been and continues to be very difficult, challenging for all of us. But I do want to state, whatever talent, whatever skill, whatever gift you have to make an impact in your industries, in your part of the world, you are the change makers. You are the innovators. Technology is not going to do that for you, Parker. Don't fire me. But the beauty of that. Thank you. The beauty of where we are now is that we're littering, literally in a place where technology does work right beside us as a digital partner. So wherever you are, whoever you are, whatever industry you represent, Agent Force is ready to join you on the journey and to help you get started faster. We have over 100 industry specific skills and actions for Agent Force. So what does an agentic future look like for you? I work with public sector. I'll give you a government example for those people who are responsible for delivering critical benefits to families. What if you had an agent that could deliver to you a proactive summary of benefit eligibility for an entire household? What would the agentic future potentially look like for our next trailblazer? That might look like creating powerful connections to help youth unlock their full potential. For over 120 years, big brothers, Big Sisters of America has been changing lives. And today they are the largest youth mentoring organization in the nation. But they're facing challenges that are common to so many of us in this room. Staffing limitations. And as a result, every year, about 5,000 youth age out of the program before being connected to a mentor. That is 5,000 missed opportunities year over year to potentially change the trajectory of a young life. And so they've turned to Agent Force to help their bigs and littles find each other faster. Take a look at this short Film.

So you want to go first?

Okay.

Oh, look at that. Was super easy.

She was shy at the beginning, like when we first started talking, but she opened up.

Did we arm wrestle?

Yeah, I think we did, but it.

Was like the first meetup.

I got it.

You did a good job.

We firmly believe that every child was born with potential, and it is our unique opportunity to help ignite it. One person, one family, one community. The domino effect of what we're able to do is truly scalable.

We have 30,000 littles that are waiting to be matched to a mentor, and our goal is to reach as many of those as fast as possible.

The goal isn't just to make a match. It's to make the right match.

That's where salesforce was introduced. We're using nonprofit cloud, what we call matchforce. All of our matching specialists go in and see exactly where they are in the process, all the way through the entire lifecycle of the relationship.

The efficiency of matchforce helps us double our output without hiring double the people. Every dollar we save is a dollar we can then turn around and reinvest back into the community.

I was thinking of maybe doing like.

Fireworks, actually, and people are watching from a boat.

Oh, that would look nice. Yeah.

We're trying to reach more young people. We're trying to do it faster, but we also need to make sure that the quality of match increases. When I heard about agentforce, I thought right away this could be a solution to reach more children. Agent force is integrated in matchforce, where all of this information on matching criteria and preferences already exist. So agentforce is helping streamline our process and elevate match recommendations at a rate that humans just can't do. Every day matters that a child doesn't have a mentor, and we expect with agentforce to be able to cut that time in half.

There is nothing more rewarding than believing in children and then watching them step up and believe in themselves.

Even impacting one child's life is worth the pursuit. I love being part of big brothers big sisters. This mission is amazing.

Treasure, you're a really important part of my life, and I just appreciate you just being here.

Gosh.

As we like to say, it takes very little to be big. And with salesforce, we are bigger.

That's an incredible story, and I'm so pleased to be able to share. The big brothers big sisters of America together is here with us in the room, and one of the stars of the film you just saw, their cto, Travis Gibson, is with us. Welcome, all of you to agent Force World Tour dc. And now we get to see all of that come to life in the form of a demo. Let's welcome back Miles and Lynn. Let's give them a hand really quickly. And while we jump in, I just want to share with you kind of a grounding statement about how we're going to approach this demo. So, Big Brothers, Big Sisters of America has three big goals. One, they want to ensure they have a vast network of volunteers. Two, they want to make those matches between bigs and littles fast. And three, most importantly, they want to make sure that those matches last. Now, the big challenge here, as I mentioned to you, is that a lot of the youth are timing or aging out of the program. So time is of the essence. So we're going to attack this demo in three parts. And let's start with vast. So it's important to have a lot of volunteer applications, but keeping our volunteers engaged throughout every part of the onboarding process is the key to success. And this is where data makes the difference. So, Tableau next, our newest analytics experience gives us the ability to assess volunteer retention patterns. And before, what we'd have to do is just dig through manual reports to try and pull out these insights. But now I can ask conversationally, why aren't my volunteers completing their applications? Now, this may not even be the most ideal question to ask. And Tableau is going to suggest to me a few more analytically correct questions so I can get to the information I actually need. And I'm going to select that first one to see where I'm seeing the highest drop off. Now, while it's analyzing this information, it'll pull back insights as well as powerful visualizations. If I want to double click. And there we have it. We see the biggest drop offs are at the interview and the background check. So why don't we go ahead and make those steps easier for everybody? And I can do that in flow. Now, what you're seeing here is an example of the volunteer application flow. And you already saw in Marianne's demo how we can streamline these types of flows with agents. So rather than building an additional conditional logic, we've already dropped in an agent that can start doing the reasoning, asking questions like, when's the last time this volunteer was engaged? What's the best way to get them re engaged? And thanks to Mulesoft connectors, we can also account for steps that we need from external systems. Now that we've updated the flow on the back end, let's see how that works from the perspective of A volunteer. So we'll flip over. And we're looking at Chris. Chris is a prospective volunteer with Big Brothers Big Sisters. He's completed his application, but not his interview. And we now know that's one of the big drop off points, thanks to our updated flow. Agent 4 steps in, detects his inactivity, sends him a prompt right here in WhatsApp, which is where he prefers to communicate. And in one tap, he can schedule that interview. No phone calls, no forms, no back and forth. That keeps the Big Brothers Big Sisters employees and staff free to focus on the big things and not the routine things. So now we've seen how AgentForce is helping with the onboarding process. Let's move on to our second step of fast making those matches. And here we are in matchforce. This is the match management system built on sales cloud. The good news now is that Chris is officially a Big. He's completed all of his steps and now we get a chance to match. This is probably the most important part of the process. It's also a good place for us to pause and emphasize the importance of the human engagement. We're talking about humans and agents. The reality is our match specialists have experience, insight, intuition that can't be replaced. But we're just making their job a whole lot easier. So with Agent Force working alongside them, the agent can go through and analyze reams of data that normally they would have to all the interview notes, all the documentation, the preferences, the interests and all those sorts of things, and then deliver up high quality recommendations for matches. And at 92%, Ethan looks like he'll be a pretty good match. So let's go ahead and put them together. So while Agent Force is working on that, let's move on to our final step, which is where we start to measure success. How do we know we've done well? Well, did the match last? Let's fast forward. We're looking at Chris again, but this time in Slack. So Big Brothers Big Sisters uses Slack to keep their bigs and littles connected. This is where they converse with one another. And this is where they access valuable resources from the organization. And because it's FERPA compliant, all their correspondence is private and secure. Today, Chris is using Slack AI to rehash their last year and a half together. And using conversation summaries, you can see he's able to surface some of their big moments, celebratory moments like Ethan's science fair win, and even some of the goals that they established at the onset of their relationship, like improving Ethan's grades. And just like that, they've hit their 18 month milestone. And based upon how things are going, they're very likely to have a lot more milestones ahead of them. Thanks to Agent Force, Big brothers Big sisters of America is building a vast network of volunteers. They're making those matches fast and with much more accuracy. And with humans and agents, they're creating life changing connections that are sure to last. One more time, thank you so much to Big brother's big sisters and Parker, back to you to wrap it up.

All right, big round of applause for John. So I love how you really lit up all the customer 360. But I gotta say selfishly, especially Slack because I've been running engineering for Slack for a year and a half now. And if you want to use agents for employee facing use cases, I guarantee you Slack is going to be the best place for you to do that. That's just a little plug for me. All right, AgentForce. So you saw the platform, you saw Data Cloud, you saw the customer360, you saw how to build AgentForce agents. That's a lot. But you know what, how do you get started? Well, simple. Start simple. This AI is like so cool right now. It's like, oh, can you do this? I can do this. And look, I could do this. We're gonna show like, we show like amazing demos, but start simply, just start and build an agent to answer questions. That's what we did at Salesforce on our website.

The first thing we did is just.

Just answer simple questions. A human could read the website, they could read all the product docs. A lot better experience to go to the agent and just ask a natural language query and get a really nice answer. What is agent for us? How does Data Cloud work? What does it cost? Is it available in this edition? All those kind of questions, simple questions. Then move on to ask the agent to do something and have the agent program the agent to actually take action based upon an action based upon a reaction. And then the scary part, but it's actually really cool. Move on to proactive action where the agent actually will do work on your behalf. That is when it's really cool. That's really when you see the power of humans and AI working together. All right, well how are you going to figure this out? Like I said earlier in the show, you can do this today for free. Go online, get a Developer Edition account, start using Agent Force, start using Data Cloud. And if you want to know how to start learning, you know this, go to trailhead,.com and become an Agent Blazer champion. Level one, level two, level three. We want one million Agent Blazers and it starts with each and every one of you in the room, in the overflow and online. So get started. The show here is not over. The keynote's over. This is the keynote. The show is not over. There is a huge show going on. 110 plus sessions, 25 demos, 30 sponsors. Go to each and every one of them or send your agent to go do some of them for you here in the room. 1pm there's going to be a great another keynote by the public sector on efficiency and impact with AI. I guarantee you that's going to be really cool. Many more go build your first agent, go out to the expo and most importantly give us feedback. Tell us how we did take the survey we always would aim to improve. So give us that constructive feedback and thank you so much for being here. Enjoy the rest of the day.