TDX Bengaluru Main Keynote

All right.

Namaste India. India.

I'm Vishwa.

And I'm Aditya. And we both together welcome you to tdx. A warm very welcome to our incredible salesforce developer community. Come on, you can do better than this. Yes. This is energy that we are expecting for a conference that's come back to India after 6 long years. Awesome.

Are you ready for TDX? We are as excited as you are.

Being here in Namma Bengaluru.

We are bringing you the excitement of.

Pre keynote with a touch of interviews, fun as well as some surprises.

Are you ready for it?

And I awaited for the most best keynote ever. Okay, so Vishwa, let's start off. Tell me this. What has changed in the past six years? A lot of things that change, Aditya. For starters, we both got married. What? I mean not. Not to each other. To our better apps. Thank you for the clarification.

Okay.

So lot of things have changed in pandemic. But on a serious note, lot of things like we went from work from office to work from home. Again from work from home to a hybrid model.

And now we are back coming into work from office.

Yeah. But talking about the pandemic, one thing that has remained constant is the energy of the community. So during the pandemic the way the community came together in support of everyone is unprecedented. Like the community has done vaccine drives. They have distributed free food to all the families that have been impacted. And really showed the world what this community is all about. That's so true, Aditya.

It's amazed to see the passion and.

The resilience what this community brings together. If I remember rightly, when the pandemic hit us everything was closed and people were not getting together. But our incredible salesforce. Community leaders, if you are all a community leaders please stand up and get recognized.

Get recognized.

If you are an mvp, please stand up. Please get recognized. Golden Hoodie winners. Golden Hoodie winners, please stand up. And not the least but all the community conference organizers, please stand up and get yourself recognized. So we have seen an explosion of community conferences last year. Which is how all of us came back together after being apart for so long. Can you name a few? Vishwa. Yeah, I think Bharat Dreamin.

Architect Summit.

Yes, Architect Summit.

Are you here?

No.

Mule Dreaming and Delhi Dream In. Guys, come on. Who else? Are they there? Bangalore Dream in.

Come on.

We are in Bangalore. Hyderabad. Trailblazin. Good MC Square Vid. Dremin. See, this is a lot of conferences. And we want to thank all of the community for making this happen. Let's give a Big round of applause for everyone. All right, so talking about conferences, quick show of hands. How many of you are here for your first ever tdx?

Wow.

Amazing.

Wow.

Trust me, you're going to love this. All right, so again, show of hands. Yesterday was a holiday and all of you are here today. So be honest with me. How many of you told your managers that you're working from home? Show of hands. Okay. All right. Wave big and smile. You're on camera. We will ensure to share it with your managers. Yeah, I'm sure there are some pro developers in this crowd as well. And it's Friday and it's known for deployments. Okay, so how many of you have brought your laptop to do some deployments? See, I said you. Okay. Yeah. You might have to roll back if you deploy in such a high energy environment, but nevertheless.

Yeah.

All right, so thank you for the response. And typically when you talk about a conference like tdx, it's not always just a conference. It's more of a celebration. So it's a celebration of our product that we all love? Yes. It's a celebration of all the innovation that we do. And most importantly, it's a celebration of the community. And one way in which we celebrate the community is by sharing your story out there so that others can be inspired. And I see a lot of familiar faces in the crowd. So Vishwa, do you want to go talk to them? Yes. Let's get into the crowd and pick few people to interview them. All right. I see people tensing up already. Yeah. All right, so we have Sukesh over here. Sukesh, why don't you stand up and come with us? All right, so the reason we picked Sukesh, please face that side. Smile for the camera. All right, so by the way, are you on BTO or working from home today? Actually, I'm both.

Oh, you're both.

You're both. I'm telling both. Okay. All right, so the reason we picked Sukesh is he was back here in TDX 2019. But back then he was a student and a journey to Salesforce Aspirant. But now he's an integral part of the Bangalore community and he's encouraging a lot more students. So Sukesh, how do you feel being back here in TDX after so long? First of all, thank you everyone. And I'm so thankful to Salesforce, APAC team and especially to Vishwa. So I have enrolled for Generative Salesforce program. From then my journey started and here continues a long way. So I'm working at Tawant as a senior software engineer. Apart from that, I'm a co team member of Bengaluru Tribal Community Group and I am marketing and communication head of Bengaluru Trimen. So apart from all these things, this is the first tdx I'm attending 2019. I couldn't able to attend because I don't know what is salesforce and all, but me and Bengaluru Trialbase Community Group and Bengaluru Tamin has inspired many of the trial bears across India. And apart from that, I'm so happy and glad to be here and I'm so excited to attend this conference. Okay, thank you. That was more than 30 seconds. But so what are you looking forward to in tdx? Do you have your eye on any session, any key takeaways, networking opportunities? First of all, I'm not sure that I'll be part of this keynote, but I'm so happy and glad to be this here talking in front of everyone. And so probably I want to network with all the MVPs and product managers, attend tech sessions and give it back to the community as well. So inspire trial basis in the ecosystem. That is what we are all here. All right, thanks a lot, Sukesh. You were definitely prepared.

Thank you.

Sukesh, take your seat. How many of you Kavindra here?

Oh, I see Kavindra here.

Okay.

Everyone excited?

That's all.

Is everyone excited?

Great. Yes.

Kavindra, thank you so much for putting, helping us, putting this amazing show for us. You have been in the ecosystem for the last 18 years. You have seen this community grow. You have seen wonderful trailblazers. We just interviewed Sukesh. Do you have anyone in your mind, one person where we can go and interview them?

Wow, that's a tough question.

It's a tough question because there's thousands of you, thousands of amazing trailblazers that I can pick from. But if I must, there is one person that comes to my mind. This is a trailblazer that has the heart of the one India trailblazer community who has jumped in to help the community and Salesforce and make an impact for India also. This is a person that has mastered AI and agent force and in turn has helped others do the same. This person has gone to the meetups, Dreamforces, tdxs and many other events and really helped others, you know, share their knowledge, their knowledge and expertise to others. And this person, when I think about initiatives, things that come to my mind are trailblazer, chain, your grid equals tdx, passes through TDX Bengaluru. And this person, she is shriya Rashankar. So many great things about Shreya. Why don't you walk with me? Yeah. Aditya, let's get her onto the stage. Yeah. So Kavindra is singing all praises for you. So while we walk on the stage, why don't you start telling us a little bit about your journey into Salesforce and how you've become an integral part of the community.

So I think my. My heart is really beating very fast, so I might not be in all of my mind to speak what I have been doing. But I think this is really. I mean, it's very. I'm so thankful, first of all, Kavindra, for all the sweet words. It's very kind of you all to be recognizing a little bit of efforts that I've put in for the community. So basically one thing that I've been doing recently is the trailblazer chain. That is something really close to my heart. What happened was when we saw this TDX India coming here, I thought, obviously everybody is excited, right? So I just wanted to kind of build up that energy for everyone to be a part of this. And when I put a message on LinkedIn saying that I am attending TDX, the question should be, who's not? And that is where my hands are literally shaking. Okay. This generally doesn't happen. And I actually got a response from somebody saying that I would really want to be a part of ddx, but somehow I'm not able to make it because of XYZ constraints. And that actually hit me. I just thought we being trailblazers, we being a part of this community and we are doing better for ourselves as well as our families. Right? Why can't we just take out some time, be a part of. Do something better and be able to help people who. Who really deserve to be right? And that's where I just.

What you've done is really great and you've been doing lots of awesome work.

Thank you so much.

All right. And since Kavindra has been singing praises for you, he has got you a small little gift all the way from the US Kavindra. You want to present it to her?

Thank you so much.

We have a little surprise for you. I will hold it. What it is. Yeah. Let's look what this surprise is.

That's a golden doodie, guys.

Bigger round of applause, people. All right. There is one more small token. A golden hoodie.

Astronomy.

We are going to take one selfie.

Okay.

It's a selfie time with the crowd so we can face this way.

Yeah. Okay. Come this Way.

Wow.

All right.

Thank you.

Thank you so much.

Thank you so much, Kra. Thank you, Shreya. All right, this cover is for you in case use it. All right. That was exciting. And look at that. It's almost time for the keynote. And before we kick it off, it's actually a timeless tradition that we have where we light a lamp before starting anything significant in our lives. So in order to do that, I would like to call upon the entire Salesforce leadership that is here. So we have Arundhati ma', am, wherever she is. MK Kavindra, Sanket Sanjana, Kristoff, Kiran, Parul Amandika. All of you please join us on stage. Arun kumar. Please. No, no, no. Please come. Come with us. No, all of us. This is an auspicious occasion for us.

Sam.

It will burn your hand.

Sa.

All right. So I would request all of you to come in front of the lamp, please. Everybody in front of the lamp. Alright. So the reason that we light a lamp is to signify that any small spark of fire can actually illuminate a world of possibilities for us. And sometimes the people themselves are the fire that open up possibilities for a whole lot of people. And we have one such person among us today. Arundhati ma', am, we want to. We have a small surprise for you. MK Handing it over to you.

So is it on? Yeah.

Yeah.

All right. So you know there's a tradition in South Indian wedding. After the couples are wedded, they're asked to look at the Arundhati star as a guiding light. And also making sure that how they lead their transformed lives together. But we don't have to look very far because we'll start right here. With the same name. Yes. She's been trailblazing for over 30 years and really leading the digital transformation of many businesses in this country. And you can see here, the government of India recognized her exemplary service, awarded the Padma Shri, joined in congratulating Arundhati for this awesome award. Congrats. And a saree. That's her favorite saree. And colors too.

So.

Congrats.

Congratulations, ma'. Am. We couldn't be more proud of you. You want to say a few words?

Microphone. Can I mic?

Can we get the mic?

First of all, good morning all of you and thank you ever so much. This was actually something that they kept as a surprise. I was told there is a little moment when we won't tell you what the program is, which is very unlike them. We run through every minute of the program. So I guessed something like this, but. Well, this is well beyond what I had thought. Thank you again very much. I'm really and truly grateful and honored. And believe me, it's a moment of great humility that I have, because to get something like this not only from the government, from the country, but also from the organization that I'm serving, it's a huge amount for anybody. So I'm truly grateful.

Thank you.

All right, so thank you.

Okay. Yeah, yeah.

Thank you so much. Everyone.

Everyone.

All right, so I think it's time for the most awaited session of the day. What is it? The keynote.

Are you all ready for the keynote?

Keep your phones on silence. Make sure that you're looking at the speakers and the screen, and get ready for the keynote.

Let's get the keynote started. So who are the Agent Blazers? Well, now, that's a story. Trailblazers. They've led the way.

People who saw a mountain and said.

Hey, I'll climb it. People who saw a challenge and said.

Hey, let's solve it.

They were pioneers, innovators, visionaries. But today, Today something new is on the horizon. It's not just about blazing a trail anymore.

It's about building a world where humans.

And digital agents work together.

Where empathy meets efficiency.

Where intelligence is autonomous. We call them Agent Blazers.

A new breed of problem solvers who.

Cut through the shiny hype of AI.

And answer the real question of what AI can actually do.

I mean, what if workforces had no limits? What if customer service could feel like.

A conversation with an old friend? What if businesses could make smarter decisions in real time? Agent blazers see the future not as.

Something that happens to them, but rather something they can create. Look, we've been dreaming about agents for years.

We've seen them in the movies.

Robots, avatars, futuristic assistants.

But this, this is different.

This is real. Agents who learn your business. Agents who know your customers. Agents who can take action right when you need it most. Age of Force is about empowering people, freeing humans to focus on what really matters.

Yeah, our stuff.

The best part, the admins, the developers.

The dreamers in the Salesforce ecosystem, You're.

The ones turning this vision into reality. But Salesforce didn't just build this platform to automate tasks. No, it was built to empower you and people like you to become agent Blazers.

So who are the Agent Blazers? You are the Agent Blazers.

And the really cool part, the future, it's already here. Right now.

Foreign.

Please welcome president and CEO salesforce south asia, arundhati bhattacharya.

Good morning, everyone. Good morning again. I hope you are excited to be here because I'm thrilled. And yes, I did hear you all the last time somebody asked you the same. And I hope that this day and tomorrow will come up to your expectations and way more. Having said that, you will all agree that the pace of AI innovation today is like nothing we have seen ever before. And that's all the more reason why we need to be at events like TDS Bangalore. So let's get right down to this amazing technology. But before doing that, in the true salesforce tradition, let me first express my heartfelt gratitude and my thanks to all of y' all for turning up here. To all our customers, our trailblazers, our partners, and of course our employees, you are at the heart of it all. And it's because of you that we are here. Now, having said that, you know, this is a company that has always been guided by its values. The values, by the way, are not something that's just written on a plaque. And especially today in the age of AI, where along with the kind of excitement it has generated, it has also generated a lot of mistrust. And trust, by the way, is our greatest value. It has to remain that because we deal with data. And that data, by the way, is something that's yours. It's not ours, it's not anybody else's. We need you to believe that we give equal importance to it in order to make our customers successful and to innovate on a daily basis. This is what really drives us. And that's the kind of promise we made 25 years ago. A simple promise. 1% of our time, 1% of our products and 1% of our profits to go to the non profit sector, to the community. And you can see the impact that it has made globally. Not only are we a zero emission company, but today if you look at the impact only in India we have given more than $5.6 million. We have contributed 622,000 volunteer hours and more than 800 organizations today use our products. Not only that, what I'm really and truly happy about today is the fact that we are declaring a grant of $300,000 to Mantra for change in order to change the way that we are actually going to deliver teachers training. And this by the way, is going to impact 44,000 schools. Therefore, I have absolutely no problems in saying that I am really proud to belong to an organization that is one of the most innovative, most philanthropic and most ethical. It's what that has driven us. We truly and really have tried to imbibe the motto of Business as a platform for change and we live it every single day. Having said that, what is Salesforce doing in India? Do I really believe it's making an impact in India, starting from one small office? Today we are a huge organization with more than 13,000 direct employees and contributing $1 billion in revenues. Look at the kind of logos that we are working with. Logos that are household names that are known by all of y' all on a daily basis. Logos like Air India, Asian Paints, Royal Enfield, Imami, Godrej, you name it, and we are working with them. Along with that, we have also created a huge trailblazer community of as many as 3.9 million people. And by the way, it's these trailblazers that are at the cutting edge of innovation and helping us innovate on a regular basis. Innovation, by the way, is driven by the way technology changes. Imagine the coming of the Internet. For the first time, we could get stores that were offline online and we could make them available for customers 24 by 7 from the comfort of their rooms. Come the cloud age and we learned an entirely new way of how we could access apps. And today we have Agent Force. Agent Force will do for the workforce what the other kinds of technologies had done in order to totally change the way we do our work. Asian Force is going to impact the workforce like never before. But tell me, why is that required? It's required because customers today have learned to expect much more than what we could ever deliver earlier. They don't want any hold times. They want to be attended to 24, 7. They want their issues resolved as soon as they call. They want to talk to experts. But over and above all of this, they also want somebody to be empathetic and understanding of the problems that they are facing. But what about the companies? Are they capable of taking this on? Their workforces are limited. There are complexities in many of the questions that have to be answered. There is actually burnout in so many of their people and overall they are finding their productivity is dropping. And this is actually out of a survey that's actually shown that productivity is indeed dropping. Now, with circumstances like this, what is it that we need? What then? If workforces were not limited, if our workforces had no limits, probably that would be the way to get the best answers for all of this. And that's exactly where Asian Force comes in with its digital labor platform. This, by the way, is a trusted, deeply unified, easy to deploy platform that's also open and integrates with almost everything that you do. Agent Force, by The way does not only assist, it can also act. And therefore companies can actually meet their customers where they are. This is really the requirement of today and it's something that can impact every business in every industry. And therefore there's a quantum change in the way the workforces can actually learn to behave. Imagine if your employees are able to solve complex issues with the assistance of Agent Force. Not only that, even in their own work, say for instance, an employee uses Agent Force to assist them in actually working on their own health plan. Imagine a time like that when the employees become truly empowered and truly enabled. This is indeed something that can bring about a very big change in the way customers experience the businesses that they interact with. But let's not only talk about theory, it's good to talk about actual examples. Take for instance Hero Fincom. You also know that it's non banking financial corporation that actually gives loans. But like all other businesses, they are cyclical. There are times when the requirement for loans are really, really high and there are other times when there is average demand. Now how do you scale your workforce to take care of the peak levels at the same manner in which you are taking care of customers on average days? Well, it's possible. It's possible with Agent Force because with the help of Agent Force, they've actually brought down the amount of time they take to approve the loans from as much as two plus days to just 30 minutes. A reduction of 99%. Take another instance. Look at Air India. Air India, as you know, is flying a huge number of our customers. In fact, I flew here in Air India and it was a lovely flight for that matter. But the fact of the matter remains that when there are issues in flights, and there could be on account of technical reasons, on account of climate, which happens very often these days, the number of issues that come up for solving are huge. Whether it be rerouting of passengers, whether it be refunds, whether it be upgrades, and all of these are complex matters. Agent Force is being used by them and they are envisaging using it more and more in order to resolve all of this. But don't take my word for it. We have here somebody from Air India, Vikram Singh. And I'm very pleased and honored to call him up over here and you can listen from the horse's mouth, so to speak. Please don't mind me calling you a horse, I'm not calling you one, that's just a turn of phrase. But please come up over here and tell our people here, tell our customers, welcome. Tell our customers you Know what impact do you really see Vikram, of Agent Force in the work that you all are doing?

Well, ma', am, Agent Force is actually.

Transforming our customer service completely. Not only the things that we do, we are completely reimagining all the processes because it is a complex operation.

Ultimately.

The recent example is the refund that we tried and solved with the Agent Force. What used to take weeks is now taking just days. And it's merely because one of the human is still involved in.

Because it's a.

It's a transaction of money. But I am very, very confident that.

In about two weeks or so, once.

We are completely confident that Agent Force.

Is doing truly an immense job in.

Calculating and doing the right thing, we should be able to do it in minutes.

That would be absolutely wonderful. Imagine getting your refund back in a matter of minutes. And beyond that, Vikram, tell me, how do you see Agent 4 supporting you in your vision for the future?

Well, Air India vision is to become the world class airlines. And our, our technological vision is also to become the best technological layer lines.

And I think Agent Force resembles of what we are trying to do.

I think it will not only empower us to reduce human efforts but also rather increase our presence with digital agents along with human to, you know, to give larger and better experiences to the community, to the consumers and, and I think it'll fast track our vision.

Thank you very much.

Thank you Vikram for coming and coming.

Here and talking to us about your company. And believe me, this time when I flew Air India, the people on the flight, the crew, they were so good and so polite and so, you know, they were so, what should I say? Giving so much of attention that I was really and truly moved. And I hope as Agent Force takes off much of their drudge duty they will be able to create that human connection far more than they were able to do earlier. But with that, it's time now for me to call on stage Mulidhar Krishna Prasad. He is our president and CTO for the unified Agent Force platform. Huge round of applause for him please.

Thank you.

Welcome Murali. And thank you. Thank you for making it all the way.

Thank you. All right. As you saw what Vikram showed you and as you saw what Arundhati talked about, Digital labor is here. Now. Two years ago when we all talked about digital labor, the talk was, you know what, just use an LLM. Just throw all your documents at it. It's going to answer everything. The reality is a little more harder than that. Why? If it's public data, it's easy you can just go to ChatGPT and ask any question for the LLM that's, that's good enough. But in an enterprise you have a lot of private data and a lot of private APIs, so it's not the same. So the LLM is more like the CPU in your computer. What are you gonna do just with the cpu, right? You need a hard drive, you need peripherals, you need an operating system to kind of run it. And that's what we are building with agentforce. It starts with your data and metadata layer where you wanna be able to bring all the data that you enterprise and make sense out of it with the metadata. And then you get the AAA layer, the apps, analytics and all the metadata around it, the semantics, its sales, its marketing, its service, its health and all the APIs to be able to connect to all your systems, SAP Microsoft, whatever system that you may have. And then comes the operating system like layer which is going to then use the LLM to be able to say which APIs to call, what data to go retrieve, and then use the power of the LLM to reason and answer. But all of this, just like in a computer, comes in a box, is wrapped in our platform and the platform provides all that security, the metadata and all the CLI and the developer tooling experience on it. But like as you all know, in any enterprise you just don't have one platform, right? You have a lot of different things. So it's not just about having a trusted platform, you also need an open platform, which is why with our platform we have opened and made it extensible at all levels of the stack. That starts with the lowest level where we make our platform available in all geos possible. At the data level, we spearheaded the industry's first zero copy model where we can share data at a file level with all of the other data systems. And of course for our APIs with our power of our platform at Mulesoft, you can virtually connect to anything that exists in your enterprise. And finally, if you have your own trained LLM, you can bring that too very easily with our platform. And that's why we believe we have the industry's leading agent force platform. It starts off at the Mulesoft layer for all APIs, our Salesforce platform that gives you all that developer experience. The data cloud that binds all the data in your enterprise and with all the applications is the ones we ship or the ones that you custom build with analytics. And then Agent Force pulls all that together to give you that agentic experience for every aspect of your business. Now this is all architecture. So then your question would be like, how does it actually work? The way it works is very simple. You have a trigger. A trigger could be somebody coming to your website and asking a question. Or a trigger could be an email coming into your system, or it could be some data change, some predictive ML that predicted your customer is gonna doesn't matter what it is. The trigger basically calls into AgentForce. Then the AgentForce reasoning engine steps in, it understands what the intent is and then it has access to that entire Corpus of data, APIs and actions and then it figures out what to do and then it uses that to actually do the action. And the outcome could be an answer to your question. The outcome could be calling an API to create the refund, like as in the Air India example. But the core heart of this is that Atlas reasoning engine and we believe we have a differentiated product here. Why? Often you will hear these terms rag and everything thrown in. People would just say, you know what, just throw some documents at an LLM, it'll answer all your questions. What we learned is it's not that easy because what you have to do, just because you have some HTML documents or others, it's not good enough for you to get the answers because you need to prepare them, make them agent ready. That means really going through that pre processing stage, chunking it, enriching it with more content so that you can go retrieve because you might have a really long document and if you have a question, you're not gonna go pick up the entire document, you need to pick up chunks of it. And that's on the right side with the power of our data cloud unstructured stack that you can get. Again, that's not enough because what you then need to do is ask the questions that coming in. You need to go figure out which chunks, match your answers, then reiterate on it. Just like if I talk to Hari here, I'd be like, he asked me a question, I'd be like, oh, did you? Is that what you meant?

Right.

I refine those questions and try to get the answers. Same here is what our planner and reasoning engine does and that together constitutes the powerful AgentForce platform. Now what we have seen with our customers like Air India, Vikram talked about it. We've also seen customers like Velour see huge advantage, like 75% more accurate results and 16x faster. And we've also seen, we have now, by the way, we sold over 5,000 deals last quarter and we have thousands of customers live and what we have seen, all of them is go through a trial, like a progression. The first phase is really having your agent answer simple questions in your corpus. And that's things like, okay, what's your question like answer, Pull up the answers in the corpus, we call them knowledge agents. And then you evolve. Now you trust it, you all to the next stage which is action agents, which are things like take actions on your behalf. And then if you trust it even more, the third phase is where then you make it autonomous so it can actually work on your behalf. It can crunch those documents, it can answer emails automatically for you to do your sdr, bdrs and so on. That is a journey that we have seen customers take. And one such customer is ourselves. Now if you go today to help.salesforce.com that's something that we actually do. So you may ask that question, how do you start this agentic journey? Now on the left side you have traditional companies, you know, traditional companies with hard coded workflows with like lots of siloed data, hallucinating AI. And this right side is this awesome agent force company. What does that mean? You've reimagined every aspect of your business to be AI first, to be agent powered. That means you have a unified understanding of who your customer is and every touch point that they may have. But then there is a gap in between. We call that the chasm. Like jumping the chasm. How do you jump that chasm? You know, for decades we've gone through various transformations. I think Arundhati showed you started with the Internet, the cloud, the mobile, the SAS revolution. So many different revolutions. In every one of them it's been you, the trailblazers, who really connected that chasm, who jumped and made your company successful in that transformation. And in this transformation, it's going to be you again who are going to make that leap for your company. And so we're going to call you not trailblazers anymore, but really Agent Blazers. You're gonna blaze the trail and really agentify your company. Not just add AI to your company, Agentify, really reimagine every aspect of your business and make it better. And to make that easier, we've now started a new community of agent placers. I invite all of you to join it. And we also have a lot of new material available for you. And as developers here, I think a lot of you brought laptops too. Your question would be, okay, can I play with it? Is this just some slides that I'm seeing here? Well, I'm very happy to announce that we now have AgentForce Developer Edition available for all of you. And if you note that small, I kept telling them to put it bigger. It's free, right? As long as you keep using it every 45 days, it's free for you. It includes the entire platform that we talked about, all of the Data Cloud, AgentForce and you can play around. You're gonna see a lot of demos today. You can create all of those yourself and go convince your boss why you can become an agent force company. Now in order to also do that, I'm gonna take you through three steps. First, we're gonna understand what does it mean to agentify your work, all of your workflows and everything else. And second, we're going to actually see how you're going to go build and deploy these agents and finally how you're going to share everything you've created with the community on the first part. Now let's dig down. I kept talking about Agent Ki's changing software. What does it mean now when you build a traditional app, what do you do? We all go figure out, okay, what relational database I should use, what logic I should do with like flows and other kind of things. Deterministic. And then you spend a lot of time building a high purpose, sort of high cost, probably ui, right? That's kind of our traditional software development life cycle. But now on the other side and the Agentix software, it's going to be both structured and unstructured data. It's not just the forms that somebody fills. It's going to be all the PDF documents, the video, audio, multimodal, all of that. And in addition you're gonna start having non determinism in your workflows because somebody's asking a question to you. It's not like a fixed workflow that you can actually write for it, right? Just like we have human conversations. And you're gonna also have the ability to create multimodal and almost near zero cost UI that's personalized to every one of your experience. And like I said earlier, we ourselves have tried this. Now if you go to help Salesforce today, in fact the entire page is just an agent there. We've actually thrown out all the website before. In fact, we think that's going to be the future of website itself. Why do you need a website? You just have a box that can answer all your questions, right? Imagine the change it's going to cost. Now what we saw in just a matter of few months, once we have implemented it, We've seen over 32,000 conversations a week, it's going to go up even more. 50% reduction in escalations. 50%. Now it's not just about the cost savings we're going to get on the other side. But imagine the customer satisfaction. They're not waiting to talk to somebody, just ask a question, you have a problem, you got the answer right there. And just like that progression, I said we started with a knowledge agent and now you can also take actions like filing cases and other things as well. And this happened by indexing over 700,000 documents that we have. But that's not all. Just like your enterprise. Salesforce is also equally complex internal implementation. We had three different orgs. A sales org that the sales team manages, a service org that the service team manages, a marketing org the marketing team manages. And what we used to think we had like 250 million visitors to our website all the time. Turns out there's only 140,000 of 140k, right? And people just had different IDs, different email and so on. And so what we did with the power of our Agent Force platform, we implemented Data Cloud there and now we have a 360 view of everything that you do on the website. You know exactly who clicked, who watched video and everything else. And that information using the power of Data Cloud one in our Agent Force platform, we can project to all these orgs, no copy, one single copy of your data projected all the orgs. And now we have multiple agents running marketing agents, sales agents, service agents, all seeing the same copy of the data. Or if you call your human and you're talking to them, they also know exactly what you've done across all touch points of your business. And that is the power that we are able to achieve with AgentForce. But coming back, we always see this as a chat interface, right? You're still talking, you're doing this. But what if it can actually extend beyond the chat window? What if it can actually go like I talked about, really have multipurpose UI and so on. And that's why I'm happy to announce Agent Force 2DX today. What agent Force 2DX will allow you to do. It replaces that rigid logic with dynamic reasoning. Now you can add agentic commands in your flow. That means imagine you have a flow, right? You know, the traditional flow, right? You start here, you put all the boxes. One of that box can now be an agentic experience. So you're going to be able to bring in non deterministic logic within deterministic logic, or vice versa. The other thing you can also do is this thing called variables. You can actually set state in your agent and really go change the reasoning logic. The second thing is it enables you to take action with mulesoft Topic center with one single click any API, you can now make it available in an agent. That means you can talk Hindi or English to your IBM mainframe. And with the power of Heroku, you can write in any language, Ruby, Python, whatever you name it and make them available there. And with the power of data cloud's action, any change in any data, you can now trigger an agent, take response to it. And finally, on the UI side, we are gonna be allowing you to actually reuse all the LWC components that you created. Now you can use that in the agentic output. You're gonna see tableau next in the demo soon where you're gonna actually see high five analytics, actually part of your agentic responses and many more. Now you heard many, many times we've been repeating Air India how it's an agent force company, but we're going to actually show you live how they implemented AgentForce. And to do that, I'm calling Avantika on the stage.

Thank you, mk. All right. Good morning, Bengaluru. So thrilled to be here. All the way from RHQ in San Francisco and I must say my journey here was extremely smooth thanks to Air India. Just as Arundhuti experience, I also had a very smooth journey and like this personalized white glove experience as I was traveling on my way here. And as Vikram mentioned, Air India is continuing to elevate that experience even further. They're poised to become the world's best airline with technology at the forefront. Now, when we think about agents and agent force, a lot of us are typically used to interacting with agents on a website in the context of a chat window. But as MK just showed us, we are starting to bring in brand new paradigms of interacting with agents with background agents, voice agents, and servicing these agents in other channels like mobile and Slack. So to show you how Air India could totally elevate their experience with AgentForce, we're actually going to show you this completely live. And to do that, big shout out to our demo drivers, Nithin and Benny. So let's get right in. All right, so here we are in Salesforce Service Cloud and we see the customer profile for the Khana family. Now, if we look closely, we see the basic contact details for our traveler, Payal Khanna. But now we go beyond those basic details and also include information like her loyalty status, the fact that she's a platinum member. And you'll notice that we even have a new insight here that she's traveling with with a six month old infant for the very first time. Now beyond these details, we're even able to bring in live data like the flight status history, the booking events. We can even see the reward transactions and web engagement data, all thanks to Data Cloud pulling in this real time information. Now this is a lot of rich context and data. What if we could add an agentic layer on top of this and actually connect this data to Agent Force? Well, to show you that, let's go straight into our Agent builder. So here we are, this is Agent Builder and we have a various group of agents here and we've clicked into our customer support agent which is meant to help our customers with their flight and booking data. Now if we look into our agents, it has multiple topics. Let's double click into the airport data topic right here. Now this topic is meant to assist customers with any inquiries related to the airline and airport operational data. And you'll notice that this topic has several actions. One of those actions includes retrieving information from data cloud. We have another action that's actually going to gather insights from Tableau and render those on top of these topics and actions. Something brand new that we've introduced includes context variables. Now we talked about introducing some level of determinism into non deterministic workflows. We can do these with variables. So over the course of the conversation you can actually save valuable information in these variables. And it's valuable because you can actually start creating filters on top of them. So these filters include rule based logic for you to determine how to how you want to route to specific topics based on the value of that variable. For example, we may want to validate a customer's account ID before we get into seat assignments and go through that whole process. So now that we've looked at how we construct this agent, my favorite part is actually simulating this agent right here within the builder. What I can do is I can ask questions from the perspective of a customer. For example, Payal can see if her flight from Cochin is canceled, what her options are. And the agent gathers valuable information like her loyalty information, some of the flight itinerary data and offers a very personal and actionable solution for her. At the same time, I can interact from the perspective of an employee. I can ask about insights about flight delays. And this agent is going to gather data from multiple sources and we're able to leverage the power of tableau to not only provide these insights, but also visualize it in this beautiful rendering right here in that chat window. Now, this powerful functionality is pretty amazing, but you might be wondering, how does this actually work? We have all this transparency built into how the agent works. In this middle column right here, which is our plan tracer, you can see exactly as the customer identity is passed in. We start by retrieving important account details, like the fact that Pyle is a valued area customer. Then we're able to fetch real time information from data cloud, like the flight and booking information. And finally, we pass that entire payload over to tableau. And tableau is what helps us generate those insights, Summarize them and visualize them like what you see here. All right. It's pretty amazing that we can conversationally interact with these agents. But what if you want to take it a step further and have these agents be a little bit more proactive? Why do I always have to type or click a button to invoke these agents? Why not just have them be a little bit more proactive and react based on an event? Well, that's where we have background agents. Background agents are able to be a lot more proactive. You can invoke these agents headlessly through an API, a flow, a scheduled event. You get to decide how you want to invoke these agents. Now, the best way to show you background agents in action is with our beloved flow Builder. So let's head into Flow Builder. Now, for those of you who are flow experts, here is an example of a flow that we have here. And what it does is based on a flight itinerary, it's able to react to different changes in the flight status. Now, I mentioned experts. You all probably have experienced flows before. It's probably very clean, elegant, and simple, like what you see here. Right? Nathan, why don't we zoom out just a little bit? Just kidding. I'm sure those of you who use flow know that it can get quite unwieldy. I mean, what we see here, that's a lot of logic branches, decision trees, and conditionals. I mean, this works perfectly fine, but it can get hard to maintain scale and even debug. Now, what if we can instead leverage agents to collapse this logic and make it a lot simpler? Well, thankfully now we can actually embed agents directly into flows. That's right. Right here we actually have the exact same flow that's reacting to a status change in the itinerary. But instead of all that complicated logic we saw earlier, we are collapsing all of that into a Single decision node by the agent. All we do is we pass in the context in the form of a prompt to the agent. The agent's already equipped with a whole host of actions it can take based on the situation. And there we go. We have this intelligent reasoning node right here within the flow rather than building all the hard coded logic. Now I actually want to show you this in action in the context of Air India's mobile application. Now what we've done is we've set up this flow to be triggered as soon as there's a cancellation in the flight status. So let's go ahead and run that flow. Now when piles flight gets canceled, the agent is immediately triggered and what it does is it gathers important context about the flight cancellation data, Pyle's flight itinerary and alternative itineraries. And look, she gets a personalized notification informing her about the cancellation. She gets more context about what's happening. And you'll notice that the agent knows that she's a valued member. So it's immediately helping her get rebooked into the earliest flight possible. The agent looks at the next alternative itineraries and renders them in this very seamless UI component that you see here. So now Payal at the click of a button can reschedule her itinerary and she's all set. Now I'm sure we can agree this experience is probably far better than anything we've all experienced before with flight delays and cancellations. Now I don't know about you, but when I'm in a frenzy at an airport with a flight cancellation, I don't even have a single second to type. Well guess what? AgentForce can also work with voice through AgentForce voice. So I can actually interact with with Air India directly through voice and I'm actually going to show you what that looks like. All right, thanks Nitin. So here I am. Hopefully you all can see what I'm showing you. I am in the Air India mobile application and now I want to interact with their customer service team through voice. So I'm going to go ahead and call them up. Hello Payal, I see that you have recently rebooked your flight. Is there anything that I can help you with today? Hi, yes, I just got rebooked and I can't seem to find my gate. Your flight is departing from gate 36 at 4pm Would you like me to send you a map to the gate? Yes please, I need it pretty fast. No problem. I will send you a link in the chat now. Wow, look at that. Isn't that amazing, huge round of applause for this wonderful experience. I mean look at that, right? A new way of interacting with customer service. And Air India is really championing and pioneering this new customer service interaction paradigm in the whole airline industry. Now we just saw the customer service experience and what the passenger sees on their end. You might be curious, what about the Air India team? What about the employees? What about their side of the picture? Well, this is where the agent forest employee agents comes into the picture. Now this agent has a slightly different set of capabilities. First, within these actions we want to connect it to third party airline APIs and thankfully we can do that with the Mulesoft API catalog. Now once we connect to those APIs, the next thing we want to do is render these for our employees in a very visual manner through tableau. So here we're going to go ahead and generate this semantic layer insights. And finally our area teams normally collaborate in Slack. This is where all the action happens. So we want to continue surfacing these insights from the agent in Slack. So now let's go ahead and add all those actions to our agent and let's see this live in Slack. So here we are in Slack and as soon as the flight status changed, our agent automatically created a Slack channel and added all the right individuals to this channel including the ground teams, the crew, the customer service teams. It summarized what's happening shows a live visualization of the rebookings. It knows who on the ground team is assigned and gives them a checklist of action items. Now you might have remembered Pyle had interacted with our voice agent because she's looking for the gate. Well, our agent has created a case to tell the team that Pyle is on her way to the gate with her infant. And now as you can see, Rohan Meta from the ground team is informed that he needs to be at the gate patiently awaiting her arrival. And the Air India team is there to support Pyle and her infant as they onboard their flight to ensure a very seamless and pleasurable journey there. My friends, you have seen through Payal's journey with Air India how Air India is delivering this connected and elevated customer experience with the power of Agentforce and Agentforce 2 DX. Thank you all so much for following along. And with that I'm going to pass it back to mk.

Wasn't that amazing? You saw a lot. She went through a lot of stuff. Right? And every single thing. By the way, all these demos are really running live on an org. Okay, so nothing fake here. You saw AgentForce API, you saw how easy it was to connect all the existing APIs into that stack. You saw Tableau next. You saw the power of data cloud bringing all that data there. And you also saw how we could bring that complicated flow with structured deterministic logic. We were able to now plug in undetermined or non deterministic logic as well. That is how you can agentify every app and workflow. And because you have all that developer edition available to you, I'm going to challenge every one of you. Go try these things. Everything is available for you to go try. But then you're going to ask the next question. What is that life cycle of this agentic app experience? What do I do now, it's not like your traditional software, right? We talked about that before because there's a lot of non determinism involved. You can't even test it to see if it's returning the same text because it's going to be different. And so we have devised a new life cycle for agentic app dev. It starts with the ideating and the plan. Now you saw a lot of those agents being created, of course. Now you can use the developer Edition to go try it out yourself, or you can also use the production orgs that you may have. But the build part is the interesting one. Now it was a complex agent. Now instead of trying to actually hard code and like create those topics and everything else, we've really simplified it. We built an agent for an agent. So now you can just use that AI assistant to actually go build your whole agent. So you can literally just type English and say, go create the agent for me. Now in addition to that, you of course have all the configuration of AgentForce. You can also use the APIs and all the unstructured stack. And with Heroku app link you can write your actions in any language of your choice. Now, once you have done the build, the next step is testing. How do you test this non deterministic thing? For that we have added testing center with testing center. Again you can use AI to generate all the tests that you want. Double check that as people are asking questions, is it doing the right topic? Is it doing the right results? And then post testing you want to go deploy and you're going to see that in the demo shortly. We have now this new DevOps center where you can use either Visual or CLI to go deploy all of these agents. And finally, once you've deployed, it's not just once and done. You want to continuously observe the agent. Maybe somebody's trying to like Break your agent, somebody's giving you toxic inputs, you want to be alerted on it. So we have alerting built right in. We have full interaction explorer that can actually tell you what kind of topics are people asking and which ones are. Is the agents able to answer well and which ones they're not able to answer. And it's always on top of every one of our mind costs, right? How is it like costing too much or not? And so that's why we have digital wallet for you to be able to really understand what the cost that's going on with AgentForce. With all of this, you now have the new 2Dx life cycle for agent building and testing, deployment and monitoring. And in order to see that, I'm going to invite Christophe to the stage. Christophe.

All right, thank you so much, mk. And before we start, please welcome our amazing demo drivers, Aditya and Benny. All right, so I want to go back to Air India because they have an amazing customer loyalty program, but they want to build an agent to make it even better. And what that agent will look like, we don't know yet. We need to ideate, remember the first step of the agent development life cycle. That is why we start in a scratch org, because it's the perfect place to experiment. And to get you started, we have some amazing new tools. First, templates, they let you create all sorts of agents really easily. For example, an SDR agent or a service agent. But then my absolute favorite, the brand new AI assistants. Because here you don't have to go through all the steps of creating an agent manually. You just describe what you want the agent to do. So in this case we're going to say, hey, we want a customer loyalty agent for Air India. It should help customers manage their points, book, reward travel and that kind of thing. And just like that, AI Assistance created the agent for you. It has a name, it has a role. All that looks good. We can move to the next phase. And here you can see that AI assistance is actually generating topics. These are the jobs to be done for the agent. For example, manage points, book reward travel like we just asked. And if we dive into one of these topics, you will see that AI assistants even generated actions. Things like get points, balance or verify redemption eligibility. Now, the first one is actually a flow and the second one is an apex class. And the point here is that you don't start from scratch or we are actually using AI to scan through your org metadata and find the flows and the apex classes that you exposed as actions. And that can be part of the agent implementation. All right, next we can review the topic description and instructions and all that looks good. So next we can choose the channels and we want that agent to work in the Air India app, in Slack and in email.

Awesome.

So now we can save this. And the last thing we will do is to actually add unstructured data. So we have some PDF files that describe the rules of the loyalty program. You can upload them here in Data Cloud, but because we did it earlier, we can just select them here in the list. And now for the big reveal, we can actually click Create Agent. And just like that, we have built a fully functioning agent in just a few minutes with AI assistance. Who wants to try it? Let's try it. Yes, let's do it. Let's ask a question.

Yes.

How can I combine points with my family? Good question. So now the agent is reasoning over all the available actions and there is your detailed response. Now, how did the agent do it? Well, let's take a look at the planner. And first you see that it selected a topic manage points. That makes sense. And then it selected a bunch of actions. And after it picked the right actions, the agent is able to find out what's the best way to actually present that answer to the user. In this case, a rich card. And the good news for us developers is that we don't even have to code that card because the agent is capable of generating rich components dynamically. Things like a card or a carousel or a form. And this is going to work across channels. WhatsApp web, it's all gonna work there. And best of all, this feature is available today. You can enable it for your agent with that Toggle Enable adaptive response format.

Awesome.

So now we created an agent with Agent Builder. And we all love graphical tools, right? But I know that many of you also like the clique. Is that right?

All right.

And that is why we just added an Agent Force module to the Salesforce cli. So Aditya, how do we work with agents in the cli?

Absolutely, Christophe. So CLI fans in the crowd, give me a cheer.

Okay?

I love it. So we are going to be working with the CLI in our beloved idea, which is VS code. And what we are going to do here we are in a Salesforce project and we can run the new agent commands using the terminal right inside VS code. So let's start it off by running our first command, which is to create an agent. So what you see here is very similar to what you would have seen on the UI where you can select from A bunch of different templates, but not going to create the agent. Instead, I'm going to retrieve the agent that Christoph has just created. For this, I'm going to run the command sf, Agent, Retrieve and pass in the name of the agent that I want to retrieve. Now what this does is it pulls down all the metadata about the agent, which includes not just the agent itself, but the topics, the instructions, the actions, and puts it all inside VS code for me to either modify, commit to version control or even deploy to further environments. Right now that I have my agent inside VS code, I can make modifications to it. So what I want to do now is add a new custom action to my agent. Now in my project there's a bunch of code and I have an Apex class that lets me redeem points for launch access. Now, how can I create an action created based on this Apex class? So for that, no surprise, it's going to be another command. In this case it's going to be Generate action. And here I'm passing the name of the agent and also the name of the Apex class, using which I want to create the action. So I give the action a name. And what you're seeing here is that an action is created based on the inputs and outputs that are present in the invocable method inside my Apex class. So all of that is built right into the cli.

Awesome. Well, thank you, Aditya. And now we created an agent with low code and, and then pro code. And it's time to move to the second step of the agent development life cycle which was remember testing. Thank you.

All right.

And testing agents is going to be very different because agents are non deterministic. So Aditya, how do we do it?

All right, so agents can be tested from the CLI using what we call an Agent 4 CLI test suite. And within my project I've already created one such test suite. And to run this test, I'm going to use the command SF Agent Test Run and pass the name of the test suite. And while the test runs. Christoph, why don't you walk us through the test suite itself?

Yes. So I want you to take a look at that test case here. Because it looks very different from a traditional unit test. You are not passing traditional input variables, you are actually passing an utterance. And that is natural language. That's a question that a user may ask. And the outcome is also not a traditional return value. It's also natural language. It's the description of what a successful response should look like. Now notice too that you can't test this with a single utterance. Why? Because people are going to ask the same thing in many different ways. So we need to pass multiple utterances here. So Aditya, how did we do with the tests?

Let me check. Looks like we passed.

We passed. Okay, that's totally awesome. But what if you are a low code developer, you want the same thing testing capabilities, right? And that is exactly why we created Testing Center. So let's take a look. And this if you want is just a graphical UI on top of the same testing engine. This is why we can see the tests that we just ran in the cli. But you want to be able to create your own tests, right? So let's do that. Let's create a new test. We're going to give it a name, we're going to select the agent, provide a description. And now remember, we need to pass the test utterances, right? So what you could do is upload a CSV file and type them all in. But that looks like a lot of work. So we can also get AI to generate these test utterances, right? So let's do that. And because AI is doing all the work, we can ask to generate 2,000 of them. So we're going to have a great solid test. And now we can go ahead and generate that test case. And there we go. We generated tests with low code. So so far we built an agent, we tested the agent, it's time to deploy it. And for that we are going to go to DevOps center because this is where admins and developers work together to manage the entire release process. And the first thing that we are going to do here is pull the changes from the scratch.

Org.

And this is really my favorite part because here you realize that everything we did so far, the agent, the instructions, the topics, it's all metadata, which means that it can be part of the exact same process. All right, so now we're going to commit these changes and then we can promote this to a staging environment because guess what? We already have a fully functioning agent that your business partners, the people who ask for that agent, can start experiment with. That means that we need to start keeping an eye on that agent. What is it doing? Is it doing the right thing? Which brings us to the last phase of the agent development life cycle which was observe and observing. An agent is going to be very different as well because there are millions of users who are going to ask for millions of things. So how do we even make sense of that massive amount of data? Well, we have a new tool for that and it's called Interaction Explorer. So here we are looking at an agent that's already in production and you can see the number of sessions, you can see the number of users, I can see all my topics. So let's dive into one of these topics. And once again we are using AI to tag and categorize all these conversations. So if we dive into one of these categories, I can see all the conversations in that category. And if something doesn't look right, I can dive even deeper at the conversation level. And here I can see the number of turns, I can see the latency, I can see the quality score. And on the left I can even see the conversation itself. So there is a ton that I can see here to understand what my agent is doing. But there is one thing that I cannot see. There is one thing that nobody in this room can see and that is private customer data. And that is a good thing because developers like us, we shouldn't be able to see that. So we need to talk about data governance for a second. And the good news is that you're already protecting your data in many different ways. In Salesforce you tag PII fields, maybe you create permission sets, sharing rules, maybe you're using shield. And the good news is that all that applies when you are using agents. But we also added a lot of data, unstructured data, conversational data. That is why we just launched new native data governance capabilities in Data Cloud. As a small example, you can create a data masking policy that defines exactly who can access your data, when, where and how. Which means that if we go back to that conversation, that data masking there you have full control over it. And that is the agent development lifecycle. That is how you create, test, deploy and observe agents with agents for us. Back to you mk.

Wasn't that amazing? Great job, Kristoff. Glad to there, thank you. Now what you saw. Avantika demonstrated what is means to do agentify your app and workflow. What Kristof and Aditya showed you, how you're going to use AI itself to go create all of that. Right? We saw how to create the agent itself, how to use AI to create your testing, how to use CLI and of course AgentForce Explorer to really understand who is using Agent Force. Now for the final third step, we're going to be talking about how you can now extend this with an open ecosystem. Now if you really look at Salesforce, I talked about earlier in my talk how open and extensible we are at all levels of the stack at the data level we are open and extensible because we have the zero copy model that we have partnered with a lot of industry leading data vendors. At the infrastructure level we can now run on multiple substrates. You have our first party substrate aws. We had Alibaba for our core stack and we just announced a partnership with Google where we will be porting all of this to run on the Google substrate as well. Then comes the LLM. We already support OpenAI, Azure, OpenAI and anthropic models. And you can also bring your own custom created LLMs as well and use it in actions. Finally, on the right side, we have AppExchange. That's been our premier way in which you can share all the things that you you have created with the community and make some money as well. All of you helped us create what AppExchange is today. We have over 7,000 partners and over 9,000 apps and expert ratings and 91% of our customers use a partner. And that's why what was just 1 million installs in 2011 is now 13 million plus installs in 2024. Along the way, AppExchange supported all of it from sales to service to marketing, tableau data and everything else. But now in this agentic era, we are also going to be announcing Agent Exchange. Agent Exchange is the way you're going to be exchanging your agent force all your topics and actions. So if you publish all of those things that you saw, those awesome demo, you can now publish all of this into the Agent Exchange. Now you can easily use them in your agent as you're creating it. You can also share and sell to other people in the community. Now in order for us to actually see how this works, I'd love to invite Parul to the stage. Parul.

Thank you.

Thank you mk. And isn't it incredible everyone? Today we have seen how Air India is using Agent Force to help their customers, crew, ground staff and even their support teams. You know what, they have a vast network of partnerships and it can be very complex and arduous to manage it all. So let's see how our employee agent can help Air India manage their partnerships. Before I dive deep into the demo, I want to give a huge shout out to my demo crew, Aditya and Benny. Okay everyone, let's start here. We are in a case in service cloud. Air India is trying to onboard a new partner as their corporate partner. We need to create a contract and send it to them for e signature. Let's head over to Agent Force. We'll ask our Agent to create the contract and send it over. I'm also wondering what the agent will come up with. It's using its logical reasoning. Hmm, there we go. Our agent was able to create the order but it was not able to send the contract. Wondering why this is simply because right now our agent does not have the capability or of the E Signature workflow. So what are our options? Option one, spend endless hours and time building and debugging this E Signature workflow from scratch. Any takers there? I don't see many. Hands up. This is a wide audience wise audience. Bengaluru. So let's go ahead with our option two, which is to find a trusted solution from a trusted partner. And where do we find trusted Agentix Solutions? Agent Exchange Here is our newly launched Agent Exchange. We already have hundreds of topics, templates and actions all ready to go. You can even install one directly from here. But you know what? It gets even better. Now you can access Agent Exchange directly inside the Agent Builder right in the flow of work. Remember I wanted to add a new action. So let's go there and look. Agent Exchange directly inside Agent Builder everyone. So let's go ahead and search for an action that can create the contract and send it for us. Now this is an AI powered intent analysis search and there you see DocuSign comes up as the first recommendation. Let's deep dive into that and see. I can learn more. Look at the reviews. I can also go through all the topics and the actions. This looks perfect for my use case. Let's go ahead and install it now. What this will do is bring in the metadata in your org. Just like any other package. We see the topics, we're going to skip those. Let's go to the actions. Let's bring in all of these actions and add them to our agent. Once these actions are added, we are all ready to go. So let's go once again to our agent and ask it to create the contract and send it again for the E signature. It's using all the logical reasoning and sifting through the new actions to empower us. And there we go. The agent was able to create the contract and send it over. Let's quickly look at the plant tracer. How this got done. So first our agent was automatically able to query the order to get the details. After that it was successfully able to invoke the Create Contract action and then it invoked the E Signature workflow all by itself. That's the power of Agent Exchange. Now you can extend the capabilities of your agent with powerful and trusted actions. From ISVs directly in the flow of work. I'm sure you're all itching to create an agent. So let me show you how to package and share your agent. For that let's head over to VS Code. Here is the Airline Maharaja agent that we just created. You can see all the metadata, the agent class itself, all the metadata about the Apex classes, templates and flows. So now we can package it easily using the Agent Force cli. Let's go to command line and give our first command. We will create a template for our agent and in simple steps. There you go. The template is created. Now let us create the second generation package again. A very simple command and boom, the package is created. And that's all you need to create your agents and share them within your company or even on Agent Exchange. So everybody, this is your moment to create your agents and share it out and live and create history. Whether you are a Salesforce admin or a seasoned developer or you are starting your journey new, you can use the expertise and your creativity on Agent Exchange today. So let's build, share and innovate together. Back to you, mk.

That was awesome, Parul. Thank you again. You saw a lot that Parul demonstrated right now. You saw Agent Exchange, you saw topics, you saw packaging and how you can make all that available. Now just to conclude what we saw, we saw three things. We saw how to agentify every app and experience, how to use all the new AI based tools to go create those agents and how to extend with the open ecosystem to kind of wrap it up. I would love to invite Arundhati back on the stage.

But before she says, I thought we.

Good for us to take some selfie before all of you start disappearing. How about, how about all of you 1, 2, 3, shout Agent Blazer and then we'll take a selfie together. All right? One, two, three.

Agent Blazer.

All right, back to you.

Wow. Wasn't that absolutely amazing? Believe me, I'm equally amazed, if not more so. What do you all think? A shout out for all our presenters. And now let's get hands on with the technology. Your first stop is Trailhead. And the first stage in Trailhead is the champion stage where you learn all the fundamentals of AI and agent wars and cloud, of course, the data cloud piece. But that's not enough. You need to then go on to the really exciting innovator level. That's where you can begin to use the technology on all of your use cases. You can use and use Agent Builder and build your own custom agent. You can also deploy agentforce for all sales and service cases. And of course, how can you not then aspire for the legend stage here? Of course you will need Specialist Agent 4 Specialist certification to unlock this. By the way, our aim is to build 1 million agent blazers. And it all starts with you and you and you. In fact, with all of you. Are we willing to take on that challenge? Louder one. Yes. And we will do it. So with that, I would love to now call upon Christophe because this is a very special moment when we declare the winners of our hackathon. Christoph, please come here. And by the way, thank you.

Thank you so much, Arundhati all. On Tuesday and Wednesday we had an incredible hackathon. In fact, it was the largest agent force hackathon ever. And it was here.

Who else will you do this other than in India?

By the way, the innovation, the passion was incredible. But I know that you all want to hear the finalists, so let's take a look. All right, so the runner ups, let's start there. Automates. Congratulations, Team Automates. We had honorable mentions. The first one is for the best demo and it goes to Warpforce. Congratulations, Warpforce. The second one was for best use of slack and it goes to three agents. Congratulations, three agents. And the last one was for best use of data cloud and it goes to Team Axo. Congratulations, Team Axo. But now the big moment. I know that you all want to know the winners, so I'll need a little bit of help. A drum roll please. And the winners are. Team Curtis. Alchemists. Congratulations. Please join us on stage to be recognized. Congratulations. Congratulations. Congratulations.

Wow.

Okay, just one minute. Before you all move off with the prize money, tell me, tell me a little about your team. What's your means, what, how did you all come together and what's your team all about? Please.

Wait. Thank you. I'm really excited here. So we are from a company called Bounteous. Our team name is Bounties. AI Chemist, which kind of looks like Alchemist. We kind of, you know, envision a solution where we wanted to create a AI concierge service that cut cuts across all the industry. And we have taken a, you know, hospital, sorry, hotel situation here. And that's it.

Well, that's exactly the second question I was about to ask you. What exactly did you build in order to get the first price? I think you have more or less described, described it. So congratulations. Congratulations again, very well deserved. Thank you.

Thank you.

Okay, and with that we come to almost the close of the keynote. But let me tell you trailhead is not the only place where you will learn. Please understand that being part of this community is a huge learning experience. It's something where you learn from each other where the knowledge is shared where you do group learning and it's great to be just part of this whole huge community and to exchange with each other all of your experiences. Join us at many of these community events that that you are seeing up here. Join us at some of our world tours and believe me you will find your time well worth what you are spending and with that would just like to remind you that there is a whole lot of things that we are expecting for today and tomorrow. I am requesting all of you all to go experience the technical sessions. There's a huge campground out there for all of you to explore and don't forget to join us tomorrow for True to the Core. Thank you all of you again for being here today and being part of this really fantastic experience. Thank you.