Dreampitch: AI for a Better Tomorrow

 Auto-transcribed on Thursday, September 19, 2024.media and text playback available on this page: https://aliceapp.ai/recordings/OQ91FAM_cTiSxXay5lfrk0RDpvUqnwI7

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Speakers:

 Speaker A - 22.37%

 Speaker B - 6.18%

 Speaker C - 5.97%

 Speaker D - 1.03%

 Speaker E - 15.74%

 Speaker F - 15.41%

 Speaker G - 22.9%

 Speaker H - 1.74%

 Speaker I - 8.64%

Notes:

- Dream Pitch is one of my favorite events. We have seen so many incredible AI leaders this week. Who, like me, took Mark's advice and gotten their first waymo this week? So this has just been added to your list before you wrap up Dreamforce.- Plant Blue is providing cutting edge technology to scale our human ability to the size of the ocean. By using robots and AI, we come a long journey from research to prototypes, to a fully automated system. This year, we started our first nation scale project, scanning the entire coastline of Italy.- Mara: Walk us through how you're acquiring clients and the intersection between purpose and profit. How do you make money? Dunya: With data products. Doctor Hanna: On your last slide, talk to me a little bit about your customer acquisition strategies.- Do you have examples of how you've changed environmental policies or I practices by collecting this data thus far? Have any of the detailed policies changed as a consequence of this data right now?- Edward: There's a company that does something similar in a geo, in a low earth orbit, high res mapping of the world. How would you be able to scale this technology to have comprehensive global coverage in an equivalent way to say what planet's doing from space?- There can only be 120 24 dream pitch winner and the 2000 5250 thousand dollars dollars winner is g. Huntington. Two runners up, um, each $75,000 just for participating today. Takeaway, uh, mo and we will see you back here in 2025.

[00:00:04]  Speaker A 
Please welcome executive Vice President, global enablement salesforce, Jody Kohner. Okay. Okay. Okay. Welcome to Dream Pitch. Sign on. Yes, it is. Dream pitch. Oh, my gosh. This is one of my favorite events. Are you having a week? Are you having a week? I am having a week.

[00:00:32]  Speaker B 
Wow.

[00:00:34]  Speaker A 
We have seen so many incredible AI leaders this week. We have unleashed our, um, revolutionary new technology agent force. And who, like me, took Mark's advice and gotten their first waymo this week. Who did it? Okay, you guys, you gotta get on this. This is so much fun. And he is not lying. It is a moment. So this has just been added to your list before you wrap up Dreamforce. Okay. All right. But before we get to that, I love this event so much. This is my 14th Dreamforce. Yes. Thank you. I survived. And, um. Um, this is always one of my most favorite, favorite events, because the whole event, the whole week, we do so much to show all of the impact that Salesforce is having on the world, how we're trying to make it a better place. And dream pitch is just the personification of that, where we give the opportunity to some genius minds to take this stage and really show us what they're doing with their technology to improve the world. Wow. I mean, we've seen incredible things through the years, right? Um, was anyone in the room last year for wise, the mental health app? Amazing. Yes. Well, they were just recently named to the top 20 apps for iOS and Android. Pretty cool, right? Pretty cool. We see, like, herculean amounts of creativity on this stage. Uh, in 2022, we met urchinomics, and these were folks who were going to the bottom of. You remember, they went to the bottom of the seafloor. They pull up these destructive sea urchins and turn them into premium seafood for restaurants all over the world. And then they don't stop there. They go back down to the barren sea floors, and they grow lush kelp gardens. Like, who's thinking of this? This is incredible. This is what we do at Dreamforce. Okay? So this year, no exception, we put out the call for three visionaries. And, man, did three people pick up that call. And this is going to be a great show for you today. Before we get there, though, I really want to take a moment, and I want to thank today's presenting sponsor, Deloitte Digital. Uh, yes, that's right. Deloitte. Yes. Deloitte is also the pioneer sponsor of all of Dreamforce. So let's give a very warm welcome to our chief commercial officer of, uh, Deloitte Digital, Dunya Sanawe. All right. Dunya. Yay. Junya. Ah. All right, so here we are. We have been having between Salesforce and Deloitte, we've just been having this magical relationship for years and years and years. What do you think makes this so special?

[00:03:21]  Speaker C 
We have. I think first the magic comes from our shared values, from the trust we've built over time working together, we've grown together and it's made way for innovation, for co creation. We run our business on Salesforce globally.

[00:03:38]  Speaker A 
Yes, you do.

[00:03:38]  Speaker C 
We do work for you. Implementing data cloud, amongst other things. Um, we also have this relentless focus on customer success. So we invest together. Deloitte recently made a $2 billion investment in industry advantage, which is really a commitment to take all of our sector and subsector expertise and embed it in everything we do, which includes how we work with you. So our collaboration on life sciences cloud is a great example of that. And then I would say just from a personal level, that each person in our Salesforce business has this very deep connection to Salesforce. For me, I started my career in financial services, sponsored a huge salesforce transformation, and then left because I wanted to help other executives the way that Deloitte and Salesforce help me. So this is my 12th dreamforce.

[00:04:28]  Speaker A 
Yes.

[00:04:29]  Speaker C 
So I'm super honored to be on this stage with you and in this room of trailblazers.

[00:04:34]  Speaker A 
Yeah, this is great. This is great. Well, and I love that you started with our shared values.

[00:04:38]  Speaker C 
Yes.

[00:04:38]  Speaker A 
And I know that Deloitte does a lot to help the planet, help people of the planet. Do you want to share some of those stories now?

[00:04:44]  Speaker C 
I would. One example that I love is right here in San Francisco. It's called yes SF.

[00:04:50]  Speaker A 
Yes. We got a yes sf in the home. Yeah.

[00:04:53]  Speaker C 
There was actually a discussion that happened right here at Dreamforce between Deloitte Salesforce City, the World Economic Forum, and the San Francisco Chamber. And the group was really talking about how San Francisco had not recovered from the, uh, pandemic as fast as other cities. And so the team was talking and said, how do we harness the spirit of entrepreneurship that really lives in this city and connect it to sustainability and equity? And yes, SF was born. Last year, we launched our first challenge and we selected 14 innovators that are already deploying their solutions, um, in areas like clean energy, vertical farming, which is really exciting. A few weeks back, we actually opened our physical location, which is on 220 Montgomery street. And it's really this place for creativity and connection and of course, action. And at that same time, we launched our second challenge um, so for all of the innovators and the entrepreneurs that are in this room, if you've got ideas that are viable and scalable to advance sustainability in San Francisco, we're accepting applications through November 4.

[00:06:03]  Speaker A 
Okay, I like that plug. Yeah, I like that. Yes sf. Yes sf. Okay, well, yes sf. Doing great work. Also super fun to say. Yes sf. Uh, you should say it.

[00:06:11]  Speaker C 
Yes.

[00:06:11]  Speaker A 
Yes sf. Yes sf. Okay, let's roll the yes sf video.

[00:06:39]  Speaker D 
M uplink and yes San Francisco are critical because I'm opened up to this entirely new network of humans that can help me do the same work that I did in New York in an entirely different geographic space. And then that's what can help basically seed these ideas across countries.

[00:07:02]  Speaker B 
It's bringing together stakeholders from policy, from other innovators, from startups, all collectively tackling a very big problem together.

[00:07:15]  Speaker D 
But we need to be bullish. We can't be shy. We can't be slow. We need to try things. We have the tools. We have everything we need to make these changes happen, and we need to do it with immediacy.

[00:07:44]  Speaker A 
Amazing. All right, well, thank you.

[00:07:46]  Speaker E 
You're welcome.

[00:07:47]  Speaker A 
All right, well, being chief commercial officer is a pretty big deal, but it's not as big of a deal as being a judge at Dream Pitch.

[00:07:53]  Speaker C 
This is true.

[00:07:53]  Speaker A 
This is a very serious gig. So why don't you take a seat? And we will also introduce. Are you ready to meet our next judges? Yes. Let's welcome them warmly. Okay. First up, uh, from Salesforce, we have our global head of VC and startups, Mara Larson. Richard. Woohoo. All right, Mara, thank you for joining us today. Thank you for joining us. All right, next we have the unbelievable founder and chief strategic officer of Zec, the mega, uh, award winning actor, filmmaker, changemaker. Please welcome entrepreneur Edward Norton.

[00:08:41]  Speaker F 
Welcome to the stage.

[00:08:42]  Speaker A 
I know it's a long walk. It's a long walk. It's a long walk. It's good. All right, and last but certainly not least, we have the co founder of Cost Plus Drugs. We have my family's personal favorite, shark on shark tank. The man, the myth, the fabric himself are cuban. All right, are you guys feeling the dream? Force, energy.

[00:09:09]  Speaker C 
We're ready.

[00:09:10]  Speaker A 
Are you ready?

[00:09:10]  Speaker G 
Go.

[00:09:10]  Speaker H 
Ready?

[00:09:11]  Speaker A 
This is big. This is big. All right, I'm going to give you the t's and C's of how this is going to roll today. All right, we have three phenomenal contestants. They are going to come up here. They have five minutes to pitch you on how they are going to change the world. Okay, you are each going to get ten minutes to ask questions, to give them feedback, and you will have up to 30 points to award to them. All right, you can have ten points for innovation, you can have ten points for scalability. You can have ten points for their impact, their ability to demonstrate that AI is going to change the world. All right, you got it? 30 points. Now, I don't think you guys should be the only ones to have fun. I think we're going to up the, uh, stakes here. All right, we're going to introduce five bonus points that are going to come from all of you. So at the end, after they've all presented, you are all going to get the chance to vote and we're going to add five to the room favorite. Sound good? All right, we got this. We got judges. We thank Deloitte. We're all ready. All right, let's do this. Our first contestant, coming from the Netherlands, we have founder of, uh, excess Materials exchange, christian van Marena.

[00:10:32]  Speaker G 
Hello. Are you ready? It's going to be a lot. So, uh, my name is christian Vermaer and I'm the founder of the Excess Materials exchange, which we call a dating site for waste, where we use AI and blockchain to match what is one company's waste to what other companies can use. And in doing so, we turn trash into treasure, one match at a time. Why is this necessary? Because we found that waste typically finds love in pretty trashy places. Also a domain where the digital era hasn't dawned yet. And this is important because, did you know, and this is crazy, that 90% of all materials going into european manufacturing are not part of the final product, and 80% of those products are waste within the first six months. How on earth is this system working? Well, it doesn't. We are consuming far more resources than our planet can sustainably provide. Earth overshoot day, they call it. It's like spending money you don't have year after year after year. And this needs to stop. But there's a solution, the circular economy. And let me explain that to you in a simple example. We worked with a pharmaceutical company that makes a flu vaccine using half a million eggs each day, which then afterwards are thrown away, costing them half a million dollars a year to process. They work with us and we found that you can turn the biomass into biofuel, you can turn the shell into either cement, into the production of plastic, or in the backing of carpets, actually making them $200,000 a year. And we've done this for many different waste streams. For example, turning orange peels into soap, uh, detergent, animal feed, turning old, uh, rail tracks into construction elements. The matches are endless and the applications are infinite. Um, and the circular economy has been valued at about $100 billion today, and it will grow to $1.5 trillion by 2030. And actually, platforms drive a lot of that value. However, at the same time, it's difficult to get there. The circle economy, in a way, is stuck in the future. Lack of good quality data, lack of standard and certificates, and I think in general, incentives just to get there. That's where our platform steps in to break down those barriers where we store information with blockchain technology in what we call passports. And then we use AI to build this neural network and basically to structure the data, uh, and also use AI to find high value next uses for these material streams. Just one example where we did 18, uh, materials weighing a total of about seven Eiffel Towers that we matched, uh, and then saving CO2 emissions equal to 88 return flights from Amsterdam to San Francisco, saving enough energy to power the Bart here in this city for more than two years, and also enough water to supply beer to the city of San Francisco for the next 30 years. And so that has led us to operations all over the world. We've been valued at $20 million recently. Our users have grown 450% over the last, uh, three years and we have 5000 solution providers connected to our platform. We are industry agnostic, but we do a lot of work in the built environment, in infrastructure, uh, energy, working with companies like ABB, uh, um, cider, electric and soda, Ramco, um, and I would say as a close, one of the things that we have found, and this is one of our early, uh, supporters, if you will, pretty good company to be in is we have found that the key when it comes to making the circular economy a reality is to reduce the cost of transaction. And AI and blockchain play a huge role in that. But also, and this is really important, as we all know, that AI is a social revolution above everything else is that it democratizes knowledge and it makes a waste expert out of everyone. And so we found that to make the circular economy a success in the world, which we need in about 20 or 30 years or so, we need about half of you to be engaged, to be involved. And that's sort of my call to action, is that we can now use these tools that we have, AI blockchain, and definitely our platform to make that a reality, to get that circle economy unstuck. So we need at least half of you. So if you can all just, if you want this, come to me afterwards and we'll get you going. Thank you.

[00:15:30]  Speaker A 
Okay, I'm going to come to you first. Mark, what did you think?

[00:15:34]  Speaker I 
Why and how do you use neural networks?

[00:15:36]  Speaker G 
So what?

[00:15:36]  Speaker I 
Why and how do you use neural networks?

[00:15:39]  Speaker G 
So what is really important is to very quickly get data that is coming from all sorts of different sources into something that falls into a particular ontology. And the neural network is basically the foundation of that neural network. And then the endpoints of each neural network become the starting point for our AI tools to then find new uses for that. So in the example the eggshell, there's calcium carbonate in the shell, and that calcium carbon that then connects to cement, connects to the backing of carpets, connects to a filler in plastic production. And that's how you build this huge, vast data cloud of new connections.

[00:16:19]  Speaker I 
Couldn't you just use generative AI to determine those connections? And wouldn't you just do a vector lookup instead?

[00:16:25]  Speaker G 
The generative AI is a really good way to, um, uh, add some fuzzy matching in there. And it actually helps in a couple of ways where it can help you bridge certain, uh, either language barriers so you can look in different languages and whatnot, but also actually helps you to, you know, um, jump how different industries.

[00:16:45]  Speaker I 
Okay, so I'm back to neural network because I don't want to dominate the time. Can't you just do a lookup? Right, so if you're trying to do a m matching from your marketplace, isn't it easier just to do a lookup, you know, a vector lookup from a generative AI or just a normal database?

[00:16:58]  Speaker G 
I mean, we are using that as well, but we have found that the ontologies really help in speeding up the matchmaking.

[00:17:03]  Speaker A 
Great. Dunya?

[00:17:05]  Speaker C 
Um, great job. As you have, um, scaled globally, would love to hear how you're addressing some of the challenges that might come from diverse regulatory environments and different market conditions.

[00:17:16]  Speaker G 
Absolutely. Yeah. So we have an office in Amsterdam, in London. We just opened up our office in Saudi Arabia and in Australia. And they all have very different ways of looking at what is waste and how to deal with it, especially if you transport it across borders. In Europe, it's fairly doable now because they have this european framework. So we try, first of all, to match stuff as local as we can. Uh, not just for the environmental impact, but also just like you said, because of these regulatory, uh, challenges. But then, at the same time, we have found that governments are very willing to support this because, you know, governments, I think, are the real driver currently still for making this a reality. So when we tell them, listen, we want to ship this to another country because we can reuse it, they're usually quite, actually open to working with us, and we do a lot of work with different types of governments, but at the same time, it is really important is that we try to stay away from classifying stuff waste. And if we do that, which actually maybe happens half of the time, we can just transport it to any regular material. So then there's no issue at all.

[00:18:18]  Speaker C 
Interesting. Thank you.

[00:18:19]  Speaker B 
Okay, Edward, two, uh, quick questions. One is, um, can you explain where you guys sit within this value chain as a company? Like, what is your actual business? Are you in? How do you do it? What's your actual business within this value creation or value exchange?

[00:18:39]  Speaker G 
So we are a SaaS platform and we engage with different parts of the value chain, which is an interesting challenge in some ways, because I think what you'll see in the circle economy is that some of these value chains that we currently have in this linear economy have to be reject a little bit of. And what you will see is in the circle economy, there's much more interaction, much more smaller skills interaction. So we find ourselves being, engaging with different parts of the value chain. Some of it is with end users, because we see that these big brands, they have ESG targets, so they want their products to be to contain recycled materials or reuse parts or whatnot. But then we also work with the manufacturers to make sure they can actually deliver those products.

[00:19:20]  Speaker B 
And, um, my second question was, um, uh, sorry, go ahead. Again. Go ahead.

[00:19:28]  Speaker A 
Cool.

[00:19:29]  Speaker H 
Uh, I'm super excited about the convergence of blockchain and AI. So I think this is a really interesting proof point. Um, and you've scaled quite successfully thus far. But I'm curious about what stakeholders or partnerships you view as critical to making this globally adopted technology and how do you plan to improve with them? Um, from this point to that point.

[00:19:49]  Speaker G 
I would say the key maybe to our success is that we were able to work together with a number of very large organizations that have the organizational capacity and capability to sort of work with us in a number of open innovation tracks that allowed us to sort of nest us in their value chain and engage with different parts of their businesses. Um, and that helped us really scale. So Saudi Aramco is one of our bigger clients, Abb. We're actually now onboarding one of the largest fast food chains in the world, which an american company, um, and working with them, they have the bandwidth to really make this happen. And they give us a bit of a platform that allows us to work with their value chain and really scale sort of on the backend of what they're doing.

[00:20:31]  Speaker A 
Okay.

[00:20:32]  Speaker B 
The question I was gonna add is how much of this relies on regulatory evolution? Like, do you think that, do you see this as entirely a voluntary corporate b two b interface where you can find efficiency on one side or value on another? Or do you think that this gets, does this need a regulatory imposition of any kind to really like it?

[00:20:59]  Speaker G 
Uh, I would say this is one of the tougher questions and it's also one of the more tougher questions that we have as an organization is really, where do we fit? Are we sort of value add or are we more compliance? Uh, and I think the judge is still out on that. I think a lot of organizations see it really as a way to not only help their branding, but also improve their employee value proposition and a way to, uh, um, help with their license, uh, to grow and all of that by reducing the environment footprint. But at the same time, especially in Europe, especially in the UK these days, we're seeing that the push from the regulator is really helping our company scale. For example, in London, in the Greater London Authority, you now have to do what they would call a pre demolition audit on each building before you're allowed to take it down and build something new. That was a huge push for our platform. Like, we've grown significantly now in the UK because, you know, all these materials are now basically coming on the market and looking for a new home.

[00:21:56]  Speaker I 
Christian, if I have a company that sells billions of widgets and I have byproduct or waste, what exactly are you selling me and how much are you charging me and what do I get for it?

[00:22:06]  Speaker G 
Great question. So we are a SaaS platform. And so what we will do is that we'll take the data that you have, we'll turn it into a passport and that password we will then match to potential solution providers and we are then basically a broker.

[00:22:18]  Speaker I 
Okay, so you're taking my product, whatever. I make a widget and I got a smidgen leftover, right?

[00:22:23]  Speaker G 
Yeah.

[00:22:23]  Speaker I 
So I got a billion smidgets. Right. And so you're going to come and are you a marketplace or are you just selling me a SaaS app that in turn I can be a marketplace with the people I think are potential buyers of my smidgens? What exactly, I'm not quite sure. And how much do you charge me?

[00:22:40]  Speaker G 
Well, I mean, first of all, we love smidgets because that's basically our.

[00:22:43]  Speaker I 
We all do, right? Because everybody loves Smidgets.

[00:22:45]  Speaker G 
And so we are a broker. So we actively find solutions for you. We even help with the logistics. We even ensure.

[00:22:52]  Speaker I 
Okay, so you're a broker. You're not in the marketplace, you're a broker. And so you charge me based off of the sales you make on the out.

[00:22:58]  Speaker G 
Um, exactly.

[00:22:59]  Speaker I 
So you're a broker. Right?

[00:23:01]  Speaker G 
You're a broker.

[00:23:02]  Speaker I 
So why do you need AI and why do you need all this other stuff if you're just matching? You know, you're taking my smidgets and you already know where the smidget market is. And Edward loves smidgets. Right? And he repurposes smidgets to save the environment. You already know that. I'm trying to, uh, see if you guys are just using buzzwords or using buzzwords.

[00:23:23]  Speaker G 
That's a good question. Well, the fact turning on the heat, the fact that you're calling it smidgens already is the challenge. Right. And the AI really helps in defining what that exactly is. What potentially can we find in there? And also very quickly allows us to understand what else we can do with it and then find players that are there to take it. And that's really key.

[00:23:46]  Speaker B 
Uh, can you answer the same thing about blockchain? You've said blockchain a few times, but I'm not clear what the blockchain. Why do you need blockchain?

[00:23:53]  Speaker G 
The blockchain is a way to basically, um, how would you say, to conserve the chain of custody, prove the provenance of materials. What we're seeing now. So this is still very nascent. Right. But is that because secondary materials and recycled materials are valued more because of their environmental performance and whatnot, there is this movement that people will sort of start to game the system. And I think that's where, um, blockchain plays a role, where, in an affordable way, you can then prove that, in fact, these materials are indeed coming from a secondary source of.

[00:24:27]  Speaker B 
It's an accreditation.

[00:24:28]  Speaker G 
It's an accreditation.

[00:24:29]  Speaker B 
Got it.

[00:24:30]  Speaker G 
And we're waiting.

[00:24:30]  Speaker A 
That's time. All right, great job.

[00:24:34]  Speaker G 
Thank you.

[00:24:35]  Speaker A 
Great job.

[00:24:35]  Speaker I 
Thank you.

[00:24:37]  Speaker A 
All right, thank you. Go ahead. All right, contestant number one. Fine for $250,000. Is that our winner? I don't know. Doctor Hannah Brock would say no. So let's welcome to the stage the chief strategy officer and co founder of Plan Blue, Doctor Hannah Brock.

[00:25:10]  Speaker F 
We all know our global challenges. Climate change, food insecurity, biodiversity loss, pollution. The challenges we face are so big and we are so small. Fortunately, we have a ah, friend in this fight, the ocean. The ocean are the main thing for our atmospheric CO2 provides food for billions of people. Reefs protect valuable real estate, and the ocean is vital for our energy transition. Opens up, uh, several markets such as blue carbon, aquaculture, coastal resilience, offshore wind and many, many more, making our ocean an ocean of opportunity. We know that government, industry are already investing big money, but they are held back because the ocean is so big and we are so small and the tools we use are so very old fashioned. Please play video. We see divers here counting manually, doing point samples at plane Blue. We are providing the next generation of cutting edge technology to scale our human ability to the size of the ocean. Play video. We know more about the surface of Mars than we know about our own ocean. Why? Because the tools we use in space are, um, not working underwater. Plant blue has made them work underwater. We only have to scan once the seafloor and, uh, collect an ocean of data, uh, revealing layers and layers and layers of information, such as health, carbon stock, biodiversity. By using robots and AI, we come a long journey from research to prototypes, to a fully automated system. This year, we, uh, started our first nation scale project, scanning the entire coastline of Italy, some 4000 km. Our challenge, an ocean of data, up to two terabytes per robot per day. The only way to pick out the valuable insights is with AI. We use AI for everything from classification to mission planning, to image processing, where we remove the effect of water so clearly that we can imagine standing on the beach. Let me show you an example. We have a coastline and we have a stripe strip of our very rich, uh, data along the coastline. And let's focus on seagrass. Seagrass is very special because it can fix carbon. 2035 times more efficient than any land based plant, but only if they're healthy. So let's mine our data to see, um, if they're healthy and extrapolate them in reduced, you see, unhealthy seagrass. Let's mine the data again and look why? We detect pollution and we can help find the point source. So to whom is this of value again? Example. Governments offset carbon emission, secure, uh, food, coastal construction permits for building, maintaining harbors, cable routes, coastal protection, real estate insurance. Imagine we would do it the old way with point estimates. It's, uh, like finding a needle in the haystack. Too expensive, too slow. In other words, impossible. But let's zoom out to see the real magic of a new era of ocean data. We detected a problem. We can actually fix it. Often very small investment on land make tremendous difference in the ocean. So, armed with data, huh, one small change. We can increase biodiversity. We have actually working carbon pumps. We fisheries can recover. We can continue to build. While we are letting the ocean do its job. We executed campaigns worldwide. We are kernel, we have a high demand and we need to scale. We are raising series a and um, to meet our 50 x growth in the next four years.

[00:30:34]  Speaker A 
They are cutting you off. That's right. It's an intentional work. All right, so let's go to you. Let's start with you, Dunya. What did you think of plan b?

[00:30:43]  Speaker C 
Nice job. Doctor Hanna, question for you.

[00:30:45]  Speaker E 
Yes.

[00:30:46]  Speaker C 
On your last slide, talk to me a little bit about your customer acquisition strategies. I saw the chart with the number of leads that you've had. But walk us through how you're acquiring clients and the intersection between purpose and profit.

[00:31:00]  Speaker F 
Yes.

[00:31:01]  Speaker E 
Yeah.

[00:31:01]  Speaker F 
So, um, I think the first thing would be to answer, how do we make money? So, with data products. So we have a project, we have a data product, then we have very rich data. So we can stack other data products on the top for the same client. Then you have to understand our market. So we are in the monitoring market. That means re incurring, uh, revenue as we need to monitor over many, many years to come. Then the other stream is that those data can be also used for other clients and other, uh, blue economy sectors. And the last thing you need to know is that we are not going out, um, uh, collecting the data. This is something our partners are doing. So we are basically, uh, teaming up with very global players who are doing the operation and who are also having the client base and we support them, uh, with the data and we can focus on where we are best on data and software.

[00:32:03]  Speaker C 
Uh, so you have a partner that's actually then finding the clients for your platform.

[00:32:08]  Speaker F 
They have already, so they are very big global players, which are already very long in that area of, uh, geospatial data from the system. They have a lot of different technologies, but they lack their ground truthing data. And that's where we come in. And at the moment, um, we are in a very sweet spot because we're the only one who can offer this.

[00:32:33]  Speaker G 
Got it.

[00:32:36]  Speaker A 
Mara.

[00:32:38]  Speaker H 
Well done. Um, I'd like to hear more about how this data turns into tangible change. Do you have examples of how you've changed environmental policies or I practices by collecting this data thus far?

[00:32:52]  Speaker F 
Yeah. So we are in, uh, exchange and get often invited also to the United nations and also to verifying bodies. Uh, because of course we have to see how we find solution and we can adapt a regulation. So that is part of our work. But m we can already start selling. It's no problem because, uh, yeah, um, there's already a big demand for this kind of data and we replacing this manual work with actually fully automated system making better and faster data, better, more specific data.

[00:33:26]  Speaker H 
So have any of the detailed policies changed as a consequence of this data right now?

[00:33:32]  Speaker F 
Yeah, that is always a very slow process, of course. Yeah. But um, as I said already, there's a lot of different market niches where we are and we can already start and that is of course something on the way. Yeah. And we are in the middle of it.

[00:33:48]  Speaker A 
Okay.

[00:33:48]  Speaker E 
Edward?

[00:33:51]  Speaker B 
Um, there's a company that I was involved with called planet that does something similar in a geo, in a low earth orbit, high res mapping of the world. And their clients are a vast array of corporate intelligence, community news reporting, monitoring of all kinds. Um, how would you compare? But that, you know, that's a full orth orbit. And to get where they are now, uh, was billions of dollars of capex investment to be able to deploy the thousands and thousands of low earth orbit satellites that they've got. How I see sort of the orange submarine and the basic idea, but the coastlines of the world alone are so vast and ocean floor even more vast. How would you be able to scale this technology to have comprehensive global coverage in an equivalent way to say what planet's doing from space? You know, how do you not have this just be sort of project specific, site specific? How can you be, how can you have a truly global coverage of something.

[00:35:15]  Speaker F 
As vast as the, uh, answer for that? Because these big global companies, they have already a lot of fancy technology, but they have uh, not the resolution. So they have very big map. So for example, c class, they know where it is, but they do not know about the health status, so they cannot look in the pollution. So you don't have to like uh, measure everything. You just need, as I showed a stripe, the strip and then you can extrapolate it. So it's also about data merging.

[00:35:49]  Speaker B 
But do your cameras, like, does your technology have to make its own paths?

[00:35:55]  Speaker F 
I didn't want to tap too, uh, into it, but we take really uh, satellite technology, hyperspectral data. So we have much, much more information, uh, than a normal RGB camera. And we also combine it with different sensors so we have later hyperscubes and have this rich information where we can basically look into fingerprints of species and therefore we can automate processes which are otherwise only done manual. So.

[00:36:24]  Speaker B 
So is your. Just so I'm clear, is your technology and in your platform, your. Your AI and software IP, or is it the physical data capture mechanism itself as well? Is it is your priority?

[00:36:42]  Speaker F 
We have a payload and that we give to our partners. They have the drones. We don't have that.

[00:36:48]  Speaker B 
I see.

[00:36:48]  Speaker E 
Uh, we really.

[00:36:50]  Speaker B 
Drones and.

[00:36:51]  Speaker F 
Okay, yeah, they have drones. They have everything. And they also know how to operate at c and things like that. So we really focus on the data and the software part.

[00:37:00]  Speaker G 
Yeah, got it.

[00:37:01]  Speaker B 
Okay.

[00:37:02]  Speaker I 
So I'm guessing you use computer vision, and then you take that data, and then you accumulate it. But in order to know what the problems are, you have to have a database of the problems, right. You have to have a source of information about problems. And in order to know what the potential solutions are, you have to have a source of data for your potential solutions. Right. And then you have to integrate. You have to use that to train your models. Right. In order to be able to extrapolate. So how are you sourcing your problems that you identify and how are you sourcing your solutions? And isn't it kind of an impossible challenge right now? Because, like you said, we don't really know what all the things are at the bottom of the ocean. And to Edwards point, unless you're able to capture data so discreet that, you know, there's something, you know, smaller than the eye can see, how can you know that you're getting the right solution? That makes sense.

[00:37:51]  Speaker F 
Yeah. Uh, absolutely. So, first of all, we have a lot of, uh, in house Nuhau with that, but I think for the technical part. So we have basically our pipeline, where we can crunch from a to z the data, and then we can attach. We call it libraries, because all the ecosystems are a little bit different. So you basically teach them, um, via the library what you need to detect. So we would need to do that.

[00:38:15]  Speaker I 
But where do you search that information from? Right. Who comes up with. Here's your list of problems to look for. Right. Because if I'm hearing you right, what you're saying is, you know what's in the pipeline and what to look for. Right?

[00:38:25]  Speaker F 
Yes, absolutely.

[00:38:26]  Speaker I 
But that's. Isn't that the most. The unsolved question right now, what to look for? Because it's the first time you're exploring this territory.

[00:38:34]  Speaker F 
Yeah, that's not a problem because you have expert know how, and you basically feed that into the pipeline, and then that gets, uh, identified. So, for core reefs, for example, it's like a week. So it's rather quick.

[00:38:49]  Speaker B 
Do you have data costs? Do you have data costs? Is there cost structured to you to get the different data overlays that you need?

[00:38:57]  Speaker F 
Yeah, we lease out our unit, and then we get the data, and then we sell the data products.

[00:39:05]  Speaker B 
All right, congrats.

[00:39:06]  Speaker A 
Well done. Well done. Good job.

[00:39:09]  Speaker C 
Good job.

[00:39:10]  Speaker A 
All right, go ahead, take a seat. And then there was one. One left right here from San Francisco. Please help me welcome the co founder and chief product officer of Butler, Gianni Zenongous.

[00:39:31]  Speaker E 
Good afternoon, everyone. My name is Jenny Zen, co founder and chief product officer of Butler. Today, I want to invite you to explore how AI reviews hidden patterns in human movement, creating a healthier and more sustainable world. Our mission is simple. We want to build the most scalable privacy. First, people sensing platform, transforming how spaces respond to people. This tiny wireless sensor in my hand can be installed within seconds, helping businesses to make smarter decisions, like managing real estate, um, enhancing energy efficiency and safety. So how do we do this? Uh, it's pretty simple. We use heat with dense, only heat. Our technology uses thermal data to check people movement, identifying people, location, occupancy, and even their body postures without capturing any sensitive information. During the past few years, we've deployed over 20,000 sensors, which can cover more than 40 million sqft. By the way, that's 20 times the size of the Moscone center, where we are right now. So why Butler? Let's start with the technology you already know, and take a look through their eyes. Cameras with computer vision see everything, including who you are, what are you doing? And, uh, even if you sneak a query into a non pet friendly loan, they label and profile everything, while PR motion sensors, like the ones turning on and off your lights, often leave you in the dark while you are reading, or even worse, while you are sitting on the toilet. Here's what buffer senses during the same day. So Corgi comes in. We know it's not a human because our algorithm filters out false signatures like small animals. We use extremely low resolution, non rgb thermal data to check people movement and also detect motionless people through body temperature. And that's it. Um, just temperature ratings, ensuring privacy at the hardware level. So what happens when we scale this technology? Buildings are the largest user interface with 7 billion daily users. But they lack the smart infrastructure to reach their full potential. Data is a new goal. Butler is the shovel paving our way to a greener and smarter future. Let's take a look at this real world example. This is an office in San Francisco. People come to the office, um, have meetings before heading to lunch. But after 01:30 p.m. it becomes an empty office. You might think things will go back to normal post pandemic, but how many actually spend the same amount of time in the office as before? Um, primary working is a permanent reality, and global companies, they need real data, not assumptions, to make leasing decisions, which can save them millions of dollars per year. Apart from cost saving. Buffer is on, uh, a bigger mission, to cut down carbon emissions from six tons per person to 2.5 tons per person by 2050. Commercial buildings are vastly underutilized with the actual space per person, double the design. By optimizing hybrid working and cut down footprint, we can cut the number down to 2.51 tons per person. With real time occupancy data and integrated with demand control ventilation system, we can trim it further to 2.23 tons per person. And with smart cleaning and traffic based maintenance, we cut another 0.1 tons per person by 2050. What if we don't have to wait till 2050 to see a real impact? What if we can save the lives of the ones you love right now? That's why we introduced Butlercare last year, an ambient monitoring platform for modern senior living and home care with a strong focus on, um, privacy and proactive safety. Apart from location data and movement, we also check poses, so our system detects subtle changes, like if someone lying down in unusual, uh, spots send instant alert to caretakers for quicker responses. And in addition to real time alert, we also collect key health indicators like moving speed, bathroom frequency, and also the time taken to stand frontiers and developing algorithms, um, to understand, uh, risks and helping elderly. I believe no technology can change the world if it's not scalable and accessible to everyone. That's why since two years ago, when we first released our first product, our annual recurring revenue has grown 25 times by end of 2026. Our plan is to deploy 100,000 sensors covering more than 200 milliamps square feet. And I hope one day you will see bachelor in every single building. Thank you.

[00:45:04]  Speaker A 
All right, Gianni. Very interesting. Very interesting. Okay, Edward, what did you think?

[00:45:13]  Speaker B 
It's really interesting. I mean, you touched on the things I haven't thought about. Um, I think. Can you lean a little into why? I mean, I totally get why this is different from cameras. I get why it's different from motion sensors. Um, what is this? Is this really something that does not exist in the current landscape of all the various, you know, we go into airports, we see heat monitoring, stuff like that. Uh, is your idea that heat related monitoring has really only been deployed in highly specific niche ways and that it's a much more effective omnipresent monitoring.

[00:46:02]  Speaker E 
That's a very good question. So I think everyone sees those, um, heat image to, um, radio temperature. But that sensor needs to be very close to human body rate, the temperature. And our sensor, the angle is not to read temperature. It's to rate where people are. And they need to be installed in the ceiling at like three, 4 meters height and understand where they are. And a number of sensors need to work together, um, to not lose people when someone enters the whole space. So our company is the first company using thermal data to track people location, like in such a large scale, and the first ever wireless sensor made because of our technology.

[00:46:44]  Speaker B 
How much does each sensor cost?

[00:46:46]  Speaker E 
Um, it depends if you are direct customer or channel partners. Uh, it's a platform as a service, um, model. So we will charge you yearly subscription fee. Um, but I cannot tell you the cost now.

[00:47:02]  Speaker I 
But how does that cost compare to the alternatives? Because I agree with Edward. Right. Doing this isn't the hard part. Right. There's a lot of ways to detract, um, movement. And you can put in as many cameras as you want. Now, you can feed that into AI. It can tell you almost anything about what it sees. You know, privacy issues aside, who's sick, who's not sick, etcetera. So price is important, right, because you're competing against a variety of alternatives.

[00:47:26]  Speaker E 
Yeah.

[00:47:26]  Speaker I 
What sets you apart and what makes you more cost effective.

[00:47:29]  Speaker E 
So we are, uh, if we're looking at competitors like camera solutions, they have hardware costs, they have computing costs, which needs to process millions of pixels per frame. For our sensor, it's only under 100 pixels thermal data to process. And the hardware itself is already much cheaper than.

[00:47:49]  Speaker I 
So, uh, what you're saying is you do the processing, right, on the sensor, the data.

[00:47:54]  Speaker E 
Sorry, what's that?

[00:47:55]  Speaker I 
So are you doing. So on your sensor that's collecting all the data, right?

[00:47:59]  Speaker E 
Yeah.

[00:47:59]  Speaker I 
So you put a bunch of sensors in a building. That's how you monitor everything, right?

[00:48:03]  Speaker E 
That's how we gather data.

[00:48:04]  Speaker I 
Right. But you're saying a lot of the data is processed right in the sensor as opposed to being sent to the cloud?

[00:48:10]  Speaker E 
Yeah. Now we do cloud computing for now because we have lightweight data. We can process the data, uh, in the cloud.

[00:48:17]  Speaker I 
Okay.

[00:48:18]  Speaker E 
And our cost is much cheaper than competitors. Um, because competitors, they need to wire the sensor, they need to process a lot of data, and also their hardware is much more.

[00:48:27]  Speaker I 
So you're not wired. You're using a mesh network.

[00:48:29]  Speaker E 
Yeah, we're using mesh network.

[00:48:31]  Speaker I 
Okay, so what you're saying is kind of like a Bluetooth connection. So you're very lightweight, so you can aggregate all the different data and process it.

[00:48:38]  Speaker E 
We are actually, we invented our own, um, um, mesh network. It's similar to Bluetooth, but this is an extremely low power, real time.

[00:48:48]  Speaker I 
Yeah. With mesh network. Okay, got it.

[00:48:50]  Speaker A 
Okay, great.

[00:48:50]  Speaker C 
Dunya, Gianni, talk a little bit about the customer feedback that you've gotten already and how you're thinking about your product roadmap as smart buildings evolve.

[00:49:01]  Speaker E 
Yeah, so I think so. For our company, a lot of time, we would apply for those, uh, rfps from big companies. They would, um, call for, like, entrance for occupancy sensors. We would apply and they would evaluate, like, 20 different solutions for occupancy sensors or people sensors. And normally we are always, like the top three or two companies, uh, selected because we are wireless. Um, we are privacy friendly, and the cost is extremely cheaper, comparing to competitive costs. Uh, and I think customer likes the fact that, um, we value privacy so much, like, in the hardware, like a lot of camera solutions, they said they are privacy friendly because they don't upload images to the cloud. They do edge computing. But our sensor is like, privacy friendly by hardware, meaning we cannot capture any sensitive information. And that's very important because even if you are a building manager, you say yes to this camera solution. It's privacy friendly. One day, our, uh, employees see a camera in the ceiling, they will ask someone to get it off. That happens a lot to a lot of customers. But, sir, we really want to be part of the infrastructure of future smart building with very, uh, privacy friendly technology.

[00:50:23]  Speaker H 
Mara, uh, we're dreamforce, and I know agent force is going to revolutionize sales, um, automation. But how are you balancing the two sides of your business? Because you're selling to quite different categories, uh, and different buyers.

[00:50:39]  Speaker E 
Yeah, that's a very good question. So, fundamentally, our technology collects movement data, and by movement data, I mean people, um, location and how long they spend in each spot and the timestamps. And we can translate those data into either occupancy, either people postures and, you know, dual time, how long they spend each spot. And I would say for us, we provide the data to customers, and our customers do the integration, like, do they want to calculate utilization of the space? Do they want to automate, like, um, care stuff? So we are API first company. We sell data to the customer. And for us, it's pretty lightweight operations, and we leave the integration part to the customer and also our integrators.

[00:51:29]  Speaker A 
Okay, great job, Gianni. Good job. All right, go ahead. All right, so this is it. You all have to kind of tally them all up. You're going to hand them off to my friend here. And this is time for you now to get to cast your vote. So go ahead and pull out your phones. We're going to give you a QR code. Now listen to me before you vote, this is very important. You only get one vote. We are on the honor system here. Do you know why? Because trust is the number one value at Salesforce. Okay? So everybody gets one vote and we're gonna open the voting for two minutes.

[00:52:07]  Speaker G 
That's it.

[00:52:08]  Speaker H 
Got me?

[00:52:08]  Speaker A 
All right. Meanwhile, why don't you three come on back up here? Come on.

[00:52:12]  Speaker B 
They do the talent.

[00:52:14]  Speaker A 
Great job. Okay, so this was, this was what? Was this a little nerve wracking? Uh, yes. Feeling okay?

[00:52:20]  Speaker E 
Yeah.

[00:52:21]  Speaker F 
And I feel like, oh, I know already what I wanted to say more.

[00:52:26]  Speaker A 
Did you hit your mark? Did you hit what you wanted to say?

[00:52:28]  Speaker F 
Yeah, I had problems with the technique, so I could also, in the beginning, bring my press fast.

[00:52:36]  Speaker A 
The clicker has been, you know, the bane of many presenters existence.

[00:52:40]  Speaker F 
Yeah.

[00:52:42]  Speaker A 
How did you feel?

[00:52:43]  Speaker E 
Um, nervous.

[00:52:45]  Speaker A 
Nervous? Yeah. Yeah. Okay, but you got through it. Are you breathing better now?

[00:52:49]  Speaker E 
Yeah, I do.

[00:52:50]  Speaker A 
Okay. All right, we'll give you a little more time. You went last. How do you feel?

[00:52:53]  Speaker G 
I mean, it's great to be here. Great crowd, great energy.

[00:52:56]  Speaker A 
It is a great crowd, right? Hell, yeah. Great crowd. Great crowd. All right, now, did you get to take in anything at Dreamforce this week? Were you able to experience some of it, walk around a little bit?

[00:53:08]  Speaker G 
I was in my cone of, uh, what would you call it? Uh, practice. Yeah, exactly.

[00:53:13]  Speaker A 
Okay. Staying in the.

[00:53:14]  Speaker G 
I did a couple of things. You know, I saw a session yesterday about how AI is being used in all the salesforce product. There's a lot of stuff coming our way. It's pretty.

[00:53:24]  Speaker A 
There is. Agent force is real. The agents are here.

[00:53:26]  Speaker G 
I think a lot of people should fear for their jobs also a little bit.

[00:53:29]  Speaker A 
You think the people should feel for their jobs.

[00:53:30]  Speaker E 
Okay.

[00:53:30]  Speaker G 
Has there been anybody been present company excluded?

[00:53:34]  Speaker A 
Uh, okay. I think it's productivity. I don't know if you've seen the branding, but it's like agents and humans working together to drive customer success.

[00:53:46]  Speaker G 
There you go.

[00:53:46]  Speaker A 
There you go. There you got it. Uh, how did you guys feel? Feeling good. Did you get to take in any of Dreamforce? No, you just did a session earlier today.

[00:53:54]  Speaker E 
Yes.

[00:53:55]  Speaker A 
Yes.

[00:53:56]  Speaker I 
Love Dreamforce.

[00:53:57]  Speaker A 
We love Dreamforce. Dreamforce. Yes. Okay, I'm going to check and see how much more vamping we're going to do. All right. Now we're going to do a round of, uh, what is your favorite character? What is your favorite salesforce character? We have examples of them right behind you. We've got Einstein and Cody. We've got Astro, we've got cloudy the goat. Do we have any fan favorites? Einstein, Cody.

[00:54:23]  Speaker G 
Einstein.

[00:54:24]  Speaker A 
Einstein. Einstein's getting a lot of love this year, I gotta be honest with you.

[00:54:27]  Speaker E 
Yeah.

[00:54:28]  Speaker F 
It's so funny. Like, they were running around with all these little, um, mustache.

[00:54:35]  Speaker A 
All right, well, I'm a, I used to be a Cody person myself. I've converted. I'm now into cloudy the goat for reasons I probably shouldn't have to explain. If we get those votes tallied faster, how are we doing over there? Do we have them? Okay, someone's going to run them over here, my fellow. Are we at them? Okay, maybe we should talk about why cloudy the goat is so awesome. Who here has tried goat yoga? Have you tried goat yoga? Yes. That man. My husband right there. Yes, that's right. Goat yoga. Go.

[00:55:11]  Speaker G 
Yoga for the win.

[00:55:12]  Speaker A 
Okay, look, look, we got the memo. Who else is wearing orange pants today?

[00:55:16]  Speaker E 
Anyone?

[00:55:17]  Speaker A 
Okay, so here's what we're gonna do. Here's what we're gonna do. We are going to award someone $250,000 right now. That's pretty cool, but I heard words this week uttered that have never, ever been uttered in the hallowed forests of dreamforce before. And do you know what those words were? Under budget. Under budget. So who thinks that we should up the ante here a little bit? Yes.

[00:55:40]  Speaker C 
Yes.

[00:55:41]  Speaker A 
This might be a career limiting move, but what the hell? I'm gonna go ahead and make an executive decision. We are gonna give the two runners up, um, each $75,000 just for participating today.

[00:55:51]  Speaker F 
Does that sound good?

[00:55:52]  Speaker A 
All right, but there can only be 120 24 dream pitch winner and the 2000 5250 thousand dollars winner is g. Huntington. Woo. Congratulations. How do you feel? Look at this. You want to keep that as a souvenir? Thank you so much. Oh, baby. Woo. Look at the confetti coming down. Congratulations. I think that is a very relevant, relevant product with everything in all the RTO, the return to office. I think you've got something special there. So congratulations. And to you too. $75,000. You're not going home empty handed. That's pretty good. That's pretty good. We're going to put up a QR code if you are, ah, running a startup, if you are interested in all these types of things and you want to get yourself up on this stage or you want to figure out how to join in on the exciting parts of Salesforce ventures, there's your QR code, it'll take you to Salesforce Launchpad. Thank you. Takeaway, uh, mo and we will see you back here in 2025.