SPEAKER_00: Welcome everyone to public demo day for Launch Accelerator Cohort 32. Really excited to introduce this cohort to everyone. It's been my pleasure to work with them over the last few months, and I really can't wait to see what comes next for them. Welcome to our guest investor judges. We'll have you introduce yourselves in a moment, and also our syndicate members who are coming in as attendees. And of course, welcome to our live stream on YouTube. So for those of you who are new to this, the format is that our founders will pitch for exactly three minutes. We do time them. And then I'll take some questions from our guest investor judges today. The founders will write them down, and then they have two minutes to answer them kind of all at once, which will keep us going at a nice steady pace. At the end, I'll ask our guest investor judges to give us their top three of the seven. And we'll also ask our syndicate members to, you know, vote in a poll for their number one. And syndicate members, there is a Q&A box at the bottom of your screen. So if you have a question for a founder as they're pitching or after or any time throughout the session, go ahead and write that question in that Q&A box. And please do tag them by their name or company so that we know, and they know that it's that question's for them. So first, I would like to introduce our guest investor judges. When I call on you, can you please share with the group, your name, your firm, your average check size, and if you have a thesis. So I usually do this first name alphabetical. So Gary, we'll start with you.

SPEAKER_04: Hello, I'm Gary Beneroff from Mew Ventures. We are a commerce enablement fund. The thesis is essentially anything that removes friction from a transaction. And our average check size is between 100 and 300K.

SPEAKER_09: All right. Thanks, Gary. Katie.

SPEAKER_10: Hi, everyone. Thanks for having me. My name is Katie Stanton. I'm the founder and GP of Moxie Ventures. We are a generalist early stage venture fund. And our median check size is about 1.5 million. Thanks. Sandy.

SPEAKER_12: Hey, everyone. Thanks for having me. Sandy Cass. I manage a fund called Red Swan Ventures. Our average check size is 650K into pre-seed and seed stage companies. We invest in consumer-driven businesses. So businesses where the enterprise value is dependent, either directly or indirectly, on consumer spend or behavior.

SPEAKER_17: All right. Thanks, Sandy. And Stu.

SPEAKER_19: Hi, everyone. I'm Stu. I run Cough Drop Capital. We're a pre-seed fund. And we do 25 to 100K checks in B2B software companies.

SPEAKER_00: All right. Thanks so much. And also just want to take a moment to thank our partners for the Accelerator, Fenwick and Silicon Valley Bank. We love working with you. And thanks for everything you do for founders. And everyone on the live stream in here, if you have anyone that you want to help tune in and live, we'll drop it in the chat. The URL is launch.co slash live. All right. So as a reminder of the format, founders pitch for three minutes, and then I'll take a couple of questions from our judges and syndicate members, feel free to drop their questions in the Q&A. So without further ado, I'll bring up our first founder, and that is Linda from MasterTech.

SPEAKER_25: All right. I'm sharing my screen. Can you guys see that? Yeah, looks good. Going to count you in. Three, two, go.

SPEAKER_27: All right. Hi, we are MasterTech AI, and we're using AI to make auto repair faster, easier, and safer for shops and DIYers. Meet Will. He is an auto technician and one of our real customers that's working at Davis Repair. For his work, Will needs to be able to service any of the 60,000 unique models of vehicles that exist in the U.S. today, including the Subaru Outback that came in with a clicking engine noise. However, with current software solutions, he needs to read through a lot of full technical documents himself to find the service information that he needs. As a result, Will often just relies on his personal experience, but with the shortage of qualified technicians in the industry, vehicles are often misdiagnosed and repairs are done incorrectly. With MasterTech AI, Will just needs to enter the vehicle VIN, and MasterTech AI will aggregate thousands of service documents for this specific Subaru. With the help of our AI co-pilot, Will can easily root cause this issue by entering the symptoms of engine clicking noise. He sees all of the known issues for engine noise for this particular model. MasterTech AI then asks follow-up questions back to Will, such as, under what conditions does this clicking noise occur, to further narrow down the root cause. MasterTech AI will then confirm the diagnosis, and Will sees that there is a specific TSB that can address this issue, along with the parts necessary for the job. Based on that TSB, he then needs to perform a cylinder head replacement, and MasterTech will provide him with step-by-step factory procedures based on his level of experience. Will can also enter VIN and mileage to discover overdue services for this Subaru. With this, our shops are discovering and converting an additional $600 worth of services per vehicle. We have established a number of industry partnerships, including with Carfax for the vehicle service history data. We also have data licensing agreements for over 90 vehicle makes. We launched our B2B product in May, and since then, we have 37 shops on active monthly subscription, and one contract with an automotive technical school. Our customers love that we're making shops operate with higher accuracy and efficiency, especially as vehicles are becoming increasingly more complex. There are over 240,000 auto repair shops in the U.S., and that's just our initial ICP. To get to 10 million AR, we just need under 2,800 shops. To get to 100 million AR, just need under 28,000 shops. For our product roadmap, we plan on enhancing the OEM data with user-submitted content for confirmed fixes, essentially becoming the stock overflow for automotive repair. We also plan on leaning into voice and camera-based assistance, as well as expanding into adjacent verticals like the HVAC industry. We are the only product and market that puts intelligence on top of automotive repair data. Our team consists of myself, 17 years of engineering experience leading teams at Microsoft and Niantic. Dave and Mitch have a combined 32 years of experience in auto repair industry. Thank you. We are MasterTech AI, and we're using AI to make auto repair faster, easier, and safer for shops and DIYers.

SPEAKER_28: All right. Thanks, Linda. Let's take a couple questions from our judges. We'll start with you, Gary.

SPEAKER_04: Great pitch, Linda. I guess my first question would be around the data set.

SPEAKER_33: I imagine you need some proprietary data to stay away from the pack here. How do you do that?

SPEAKER_22: All right. We'll take another question. And, Syndicate members, just to remind you, there's a Q&A box. If you have any questions, feel free to go ahead and drop them there.

SPEAKER_37: Katie, how about you?

SPEAKER_10: Great job, Linda. I'd love to learn a little bit more about your ICP, what kinds of shops, what size of shops, locations of shops, the type of buyer, and what kind of software tools do they currently use?

SPEAKER_39: All right. Awesome. You have two minutes for those questions, Linda.

SPEAKER_41: Awesome. Yeah. Thank you so much for the questions.

SPEAKER_27: So, Gary, so regarding the data set that we have, so we have a couple of different sets of data. The primary data that we are using, which is the service data for specific vehicles. So, that is not public. That is, you know, that is something that we have to get licensing deals with OEMs through our data aggregator provider. And there is a pretty high barrier to entry to get access to this data, both in terms of the licensing costs, but also in terms of the data compliance requirements that OEMs have, because they're very sensitive to the data being used in the correct way in terms of liability or, you know, leakage of sensitive material that's trained in the public models. So, we have gotten the vast majority of the approvals that we need, and we are just securing the final two OEM data that we need right now. And the other sets of data we're integrating with shop management systems, so being able to access the shop history records, the customer records, vehicle history, et cetera. Also with Carfax, as well as our user content submission pipeline, which will be proprietary to us, so that we can enhance the platform, the more that the our users use it. So, Katie, regarding our ICP, so right now, for the market that we're targeting, the ICP is for the independent auto repair shops, you know, 240,000 of just on that side. Although there are other services, other businesses like used car dealers, automotive technical schools, as well, as well as our businesses that can use our product as well. On the independent side, we are currently targeting small to medium chains of shops, so starting sort of mid-market and then moving upmarket to the larger enterprise chains that have thousands of locations in the country, and we're already piloting in some of those larger chains.

SPEAKER_00: Okay, great job, Linda. That two minutes is going to be tough. You nailed it. All right, next up, we have Rami from Quirio, and Linda, just a reminder, there is a question for you in the Q&A box. Founders, just continue to look there and go ahead and answer those as you can. All right, Rami, can we hear you?

SPEAKER_48: Yes, can you hear me?

SPEAKER_00: I sure can. Three, two, go.

SPEAKER_48: Great.

SPEAKER_50: Nice to meet you, everybody. My name is Rami. I'm the co-founder and CEO of Quirio, and we're building data intelligence at any technical level. Oh, there. All right. So, getting useful insights from data is really expensive and slow for most companies. On one end, you have business people that understand the operation of the business, but lack the data skills to query data themselves. And on the other hand, you have data people that have all the technical skills that they need, but lack the business context. And as it turns out, most of the time spent on getting insights is to solve this telephone issue and bridge that gap between the two teams. A great example of this is one of our first customers, Enver, who was CTO of a B2B SaaS called GrowDash, and they were spending $150,000 on their data solutions. They had $60,000 for Looker, which came bundled, you know, with Google BigQuery. Everyone on the team was waiting for Enver to get any sort of insights. He was the only one that could use the tool. And he was about to hire two data analysts to unblock his team. And now he's paying us $15,000 a year to fix it, and let's see how. Instead of Enver being the only one who could use the product, his CEO, Sean, can now log into Quirio, ask a question like, what are sales for July? He knows the business, so he knows the, you know, logic for the answer was correct. Now, perhaps Sean wants to go in and make a chart to actually track sales month over month. He can go in here. Instead of looking for the data in the database, he can just prompt what he wants in the X and Y. And just like that, Sean made his first chart. He can now track sales month over month. We can bring back Enver, who wants to do something a little more technical and actually forecast sales. He can use Quirio more of a co-pilot to help him write Python in the Jupyter notebook, produce a visual that makes sense. And now they can also track if they're hitting their forecasted sales for the rest of the year. Because of this, Grow Dash was able to delay two data hires, replace Looker, and that saved them $150,000 a year. Like Looker, other products in the market are typically too technical or only for reporting. We've had customers leave other competitors like Metabase and Kibana for us, despite us not having feature parity for this exact reason. We're starting off by selling to CTOs at SaaS, logistics, and e-commerce scale-ups. Now, any company that needs the internet to run is going to need a data solution, but we are focusing in on this initial cohort. Since selling in February, we've signed about $80,000 in recurring revenue through contracts, half of which have converted from their pilot to the paid periods, and we're growing an average of 20% month over month. For the team, it's myself, Rami. I spent five years at Amazon in a mix of engineering roles at robotics, and then also a product for Alexa. My co-founder also comes from a background of both technical and business roles, except he worked for startups where he was a 2x exited operator. And that's all. Thank you guys again. And we're Quirio. We're building data intelligence for any technical level.

SPEAKER_54: All right. Thanks, Rami. Okay. Sandy, let's start with you. Question for Rami.

SPEAKER_12: Thanks, Rami. I enjoyed the pitch. As someone who ran a couple of finance teams in my prior life and spent a lot of money on Looker. Sorry. Your pitch is music to my ears. I guess, so you're targeting earlier stage startups, scale-ups. My question would be, you know, Looker is pretty robust. Do you expect that your product kind of taps out as companies get to a certain scale, or can you really grow with these companies as they get very large and complicated?

SPEAKER_22: All right. Great. And let's take one from our syndicate. Dan's asking, how do you prevent potential hallucinations of data slash answers?

SPEAKER_45: And does the user have the ability to audit the answer in some way? Two minutes for that, Rami.

SPEAKER_48: Thank you. All right. So starting with you, Sandy.

SPEAKER_50: I think data needs aren't the one-size-fits-all. I think for the foreseeable future, if you're looking for a pure SQL querying tool that has good dashboarding and has a basic data model, I think Looker is going to fit that need for a lot of companies. Now, there's a ton of other teams that like the fact that we have, you know, Python included, where they can pull the same data sets and actually do cloud Python in the same space. That's kind of a big differentiator that I think no matter how big a company gets, Looker won't fulfill that need. And I think it's going to be similar features of that, where not every data team has the same full needs for what they want as a data strategy and how much access they want to give to the rest of the company. So both the fact that we focus a lot on giving non-technical people access, plus the fact that we give data teams a Python environment, I think will continue to differentiate us from like competitors like Looker who've had a long time to do Python but haven't. And on the second part for the hallucinations that's a great question actually and about the auditing so we have this big statement where it's not trust it's transparency. You know we talked to data team it's like I don't trust this you know Ai to purely do a full career by itself, I want to make sure so. Everything that's ever written if you're using it in that co pilot or autopilot mode, you can audit and see everything that's being written. The data team can also audited for major reports and the way that we stop hallucinations is we built our own data model from scratch. You could think about it as like a different variation of dbt or look ml one that's really optimized to giving you know Ai's all the context, they need to write correct queries without overstressing the context window and not giving too much that's unnecessary. And yeah, thank you both for the questions.

SPEAKER_22: All right, great and keep an eye out in the Q&A box in case you get any additional hi Jason. So you're putting comments in this chat there is awesome.

SPEAKER_62: Yeah, yeah, instead of interrupting anybody I'll just give my candid thoughts in the chat. For those of you following along and the first two companies are just so strong. We're getting these incredible teams, because the number of people applying to our programs in the last two years has gone four or five x. In other words, the all in effect as a hit our application so we have so many applications. Just we're being incredibly selective in picking two or three person technical teams with product velocity and man the traction has been fantastic. These are all year one companies, year zero companies, and just so exciting to see what people are building with Ai and how fast they're moving and how quickly people are giving them money, which is great. All right.

SPEAKER_64: All right. Let's keep going. Let's keep going.

SPEAKER_00: Next up, Mark from Convertmate.

SPEAKER_66: Hey, hi everybody. Sounds good.

SPEAKER_00: Three, two, go.

SPEAKER_67: So I'm Mark, co-founder of Convertmate, and we make e-commerce SEO easy. So why do we do this? In recent years, retailers have relied on paid acquisitions to get traffic and shoppers to their websites. So mainly Meta and Google ads. But with cost of acquisitions rising, their profits are going down and this puts their business at risk. So this was the case for Gary, the owner of a large costume store in Australia. His team had no time or knowledge to do SEO, so they overinvested in ads. So they came to us for help. Convertmate automates the manual SEO work that all e-commerce companies need to do. The first thing Convertmate does is run a keyword research on Gary's entire product listing. We use our Google Search Console integration to target the exact keyword that will bring most traffic to his products. Convertmate then integrates that keyword into his product and collection copy. Gary's team can review the changes one by one or by batch, and we do this monthly. Convertmate also creates blog articles on long-tail keywords with internal linking to his products. So this boosts search rankings. And for the target keyword clueless costume, Gary's product appears first in his target market of Australia. And this is the case across most of his products. So the results have been tremendous. He tripled his organic traffic, and that's an additional 8k in sales per month. But most importantly, this is high profit sales. And we're just getting started. Today Convertmate enriches product data for the products to rank high in Google. But we're going to be rolling out all the channels that our clients use, paid or organic. So Google Merchant Center, Meta, TikTok, starting with Google Merchant Center this month. And applying the same logic, enriching product data so it ranks high at a lower cost. We'll also be integrating with all major e-com platforms. So we're B2B SaaS with three plans. We're growing fast. We doubled our prices in September. And on the back of that, we've already gone 39% to 12.7k MRR in October. Our go-to market is based mainly on marketing. We're very good at SEO. So we have a lot of free content that brings leads to our SaaS. We also work with partners via a white label offer and a referral scheme. And we do outbound sales. Our broader vision is to go after the product information market. And our main differentiator is that we enrich product data with AI for the products to rank high in each channels of distribution. And we have constant feed improvement, which means that every month we adapt the product to make sure it ranks high for every channel. We're the team to do this. I spent eight years in e-commerce SaaS enterprise sales. And Boris has created a e-commerce platform with hundreds of retailers on it prior to Convermate. And together we Convermate and we make e-commerce SEO easy. Thank you for your time and your questions.

SPEAKER_54: All right. Thanks, Mark. Stu, we'll start with you. Question for Mark.

SPEAKER_75: Hey, Mark. Great pitch. How do you make sure that your product is an ongoing need versus sort of, you know, providing a one-time lift in sales? How do you make sure that it's an ongoing use case?

SPEAKER_78: All right, great. Back around the horn. Another one from you, Gary.

SPEAKER_04: Yeah, two questions for you. The first is how does the product differentiate from a Yoast or some of the other guys are doing, you know, SEO product enrichment and have for a long time? And then why do you want to go into the PIM market?

SPEAKER_33: I think PIM is broken, but it is somewhat slow growing. And I'm curious why that's the roadmap.

SPEAKER_81: All right. Two minutes for those, Mark. Thanks.

SPEAKER_67: Yeah. Thank you both for your questions. So, Stu, to start with your question, how do we make our product an ongoing need? So there's three ways we do this. The first is, so SEO is ever-changing, depending on the season, on the search requests. So we're going to adapt continuously products to match user intent, to make sure that the printing strength high. So it's not a one-time lift. It needs to be updated continuously. The second aspect is that our clients, they add a lot of products. So that means that, you know, their retailers, they're going to add 100, 200 products per month. So we're going to, you know, ongoing help them do this. And the third reason is that SEO is also about topical authority. So our work in the long term is going to improve that topical authority of the store and have it rank higher overall. So, Gary, for your questions, which are great questions. So in terms of how we differentiate on the, in comparison to other Shopify apps or SEO tools, I would say that the main aspect is transparency. We're extremely transparent with our users into why we're doing the changes. So we feed from a lot of different data sources, mainly Google Merchant Center and third-party SEO data. And we're extremely transparent all along the process, telling clients why we do this and why it's going to help them. And we see that that's what our clients love about working with us. They see the results. They understand why we're making the changes. And in terms of going after the product information markets, I think the reason we're going after that market is, as you said, for this reason, it's a broken market. That being said, retailers have always new channels to go after, right? Currently, we're shopping on websites. Tomorrow, we're going to shop on TikTok on, you know, we're already shopping on Amazon or any, any new channel. So I think we think it's broken and we want to do what Zapier did to integration. It's really to go after that market and shake it a bit and, and, and help our clients. Thanks for, for your questions.

SPEAKER_84: All right. Got it in two. Well done, Mark. Next up, we have Alexander from Ellis.

SPEAKER_78: And Mark, there's another question for you in the Q&A. Founders, please keep checking that box.

SPEAKER_86: One thing I just wanted to add there, Jackie, if I may. Sure. Can you hear me? Okay. Yep. Is one of the things we like to do is look at tools and then ask, how do they become platforms?

SPEAKER_88: And we work with our founders a lot on that because they find some really great beachhead. They get this wedge strategy. They start getting a bunch of people, you know, getting great value from it. And then we like to see them open that wedge up. Right. And really split the log in. So if you go to the features page at Convertmate, that's where I get super excited because it's any product optimized continuously anywhere. And if you look at how I'm on the board of a fashion company called Lashify, and one of the biggest hurdles we have is optimizing Amazon, optimizing Shopify. What do we do about the TikTok shop? What do we do about this new shop? What do we do about content modules? And so we have kind of made one of our specialities here is looking at these great toolkits and then saying, how do you make it more sticky and impossible for somebody to unsubscribe? And yeah. Anyway, I just thought I would add that because it's something that I think Stu pointed out and it comes up quite often.

SPEAKER_90: Thanks, Jason. All right. Alexander, you're up. Can we hear you?

SPEAKER_92: Yes. Hey, everyone. I'm Alexander, the co-founder and CEO of Ellis, and we are building the Salesforce for startups. Meet Samuk. Samuk is the founder and CTO of Weave, which is a design as a services company based here to San Francisco. And Samuk is going to walk us through what he used to have to do to set up cold email before he started using Ellis. First, Samuk would go and register a domain on one of these registrars, set it up for email marketing. Then he would go to Google or Microsoft and get a new inbox. And then he would connect that to instantly or warm up to warm that inbox up. Now Samuk has to go to Mailchimp, SendGrid, and HubSpot to set up the sending and sequencing for his email campaign. And then now Weave has to buy a B2B contact database like ZoomInfo or Apollo to get the list of people they want to target. Samuk, as the CTO, spends the time to write the code and glue all this together and has to pay contractors over $3,000 a month to maintain this system. Here's how this works today in Ellis. Samuk logs onto the platform and Ellis will suggest similar domains to register for him. He chooses one he likes, configures it to redirect to his landing page, enters in the inbox name he wants, and that's it. With one click, we replace all the point solutions I mentioned. So with one click, two days of manual setup is done. But setup isn't what actually makes an email campaign convert and it isn't going to get Weave new customers. What Samuk now needs to do is much harder. Write super personalized, super engaging emails. Well, Ellis helps with that too. Samuk logs onto the platform and enters in what he wants to focus on in this campaign. What makes Weave special? Weave sells to startups and gives them an entire design team. They also combine marketing and app design so startups can have a unified design experience. Samuk is also providing a free design audit as part of this campaign. Samuk will adjust the tone of the email so it sounds like something that he likes. And when he clicks generate, we pull data from our integrated CRM, our private data sources, and any information we can get on these people and craft a super personalized, super engaging email for every single person. So to recap, two days of manual setup is done with one click. We don't do templates. We do AI hyper personalization. Less than one in a thousand of our emails go to spam. And at the end of the day, that's a 5x better conversion rate for our customers. For Samuk, that meant he landed a five-figure MRR customer in his first month on his first campaign using Ellis. But this cold email stuff is just a start. What we're really building is a CRM that actually helps you get customers. It's going to handle inbound, outbound, and all CRM operations that you expect. Right now, we charge $100, $500, and $2,000 a month for our platform, and we're aggressively moving up market. We have 23 startups and an enterprise pilot, and our MRR has grown 60% month over month from $400 to over $3,000. Our competition is mostly point-to-point solutions that require manual setup and enterprise platforms that are really for scaling out in enterprise sales teams. You would never see a scale-up using Salesforce or HubSpot, and if they do, they definitely don't like it. There are AI BDRs out there, but they're missing the point of the data mode. They don't have the CRM data to help really personalize emails and really drive automation. To get to $1 million in ARR, we want to sustain our 60% month-over-month growth. To get to $10 million in ARR, we're aggressively moving up market, targeting enterprise customers and scale-ups, and to get to $100 million in ARR, we need to win less than 1% of annual CRM spend. We're two ex-Uber, ex-Tinder engineers that want to help startups get customers. I'm happy to answer any questions you guys have.

SPEAKER_23: All right. Thanks, Alexander. Katie, we'll start with you. Question for Alexander.

SPEAKER_10: Yeah, great pitch. You're going to hear a recurring theme with me. I'd love to learn a little bit more about that ICP. How do you get 10,000 SAMUKS, and what are their titles, and what is really broken for them? So how do you get them off of Salesforce and HubSpot?

SPEAKER_96: Great. How about you, Sandy?

SPEAKER_12: Yeah, my questions are similar. You know, we've seen a lot of pitches using AI to replace Salesforce, HubSpot, et cetera. Really, I think one wanted to understand what's the mode here, and two, to Jason's point, like, is there maybe a strategy where you go in with a specific industry vertical, own that wedge, and then expand to other industries? So, again, talking to the ICP. All right.

SPEAKER_99: Two minutes for that, Alexander. Thanks.

SPEAKER_92: Thank you so much for your questions. Katie, I love your question. So, our ICP has always been startups and startup founders, but we're aggressively moving to target scale-ups, and you'll typically see ahead of business development, a chief marketing officer that needs to get a lot done, needs to target a lot more channels, needs to do more outbound, but doesn't have the budget to hire a bunch of BDRs, and so they're super frustrated that Salesforce requires a lot of setup. They're super frustrated that you need to hire someone to manually set it up. It takes a long time. It's very expensive, and then we come to them and tell them, we can set it up for you. You won't need to hire more BDRs to do data entry. Everything is automated, and you can use this for automating your outbound and your inbound marketing, so it's a very easy sale to them because we're better, faster, and we're cheaper. Sandy, I love your questions. You know, we started off as an email marketing platform really thinking about what that moat is to keep customers, and we think the most important thing is a data moat. So as the people use our outbound marketing platform and start to use our CRM, all of their customer data starts to flow into our platform. They start to get, their teams start to get used to having all of our automations, and that gives us really good staying power. So really, it's about having a data moat.

SPEAKER_94: All right. Thanks, Alexander. Next up, we have Chef from Chef Reactions.

SPEAKER_00: You ready to go, Chef?

SPEAKER_105: I am ready. Can you hear me?

SPEAKER_00: Yeah, sure can. I'm going to count you in. Three, two, go.

SPEAKER_106: Hi, I'm Chef Reactions, a former chef turned content creator, and I'm here to talk to you about my company, Back of House Spice Company. Two years ago, I put down the knife and picked up the phone and started doing reactions to online cooking videos. Since then, I've grown an audience and community of 6 million people across all platforms with over 10 billion views. Here's a little compilation in case you're unfamiliar.

SPEAKER_110: I learned this in Texas.

SPEAKER_113: Nah, no, you didn't. A dog bow sauce, because it's for dogs. Okay, a couple bags of little smokies. Ooh, they're wet. All right, we need something like this. We need a timeline cleanse. It says 0.003 out of 10. 10 out of 10, good puppies. It's one out of 10. I definitely, I definitely eat some fuck. 10 out of 10 would devour.

SPEAKER_106: I've also branched out into doing longer form content on my YouTube channel, doing product reviews, hotel reviews, and restaurant reviews. I've been fortunate enough to work with some of the largest brands in the world and most recently completely sold out of an apron collaboration with Headley and Bennett. So I guess that kind of makes me an influencer now. Kim Kardashian has Skims, Mr. Beast has Feastables, and Emma Chamberlain has Chamberlain Coffee. And to be honest with you, I'm not quite sure who she is. Having said that, I'm now launching Back of House Spice Company, a kitchen culture-based line of premium spice blends with bold, authentic flavors that bring out your inner chef. I chose spices because it's always been a passion of mine to add flavor into people's lives and to make people better cooks. Adding some spice is the easiest way to do so. Also, in 2020, I did an experiment selling $8,000 worth of spice blends from my basement. People love the bold flavors. It doesn't hurt that spices have a very long shelf life for a fruit park as well. Our spice blends are made by chefs for everyone. Our spices are high in quality, freshly ground, non-GMO, gluten-free, vegan, and kosher. Our spice blends are bold in flavor, authentic, and respectful to the cultures they originate from. We're going to package in eco-friendly milk cartons that are easy to store and easy to pour. Our bold color palette and playful artwork will help us stand out from a crowd of brown bags and plastic shakers. We're also going to do limited merch drops of kitchen essentials and clothing to engage with our community and expand the brand. Launching with three blends, as well as a finishing salt and a cracked black pepper blend, we'll look to introduce more SKUs periodically. We're going to collaborate with our network of food creators for content, as well as send out influencer packs prior to launch. Once our branding guidelines are finalized, we're going to start collecting emails to build a subscriber list for newsletters. We're going to start with direct-to-consumer, and we're going to partner with a centrally located co-packer to ensure quality control and efficient fulfillment with an eye to eventually move into retail. As I mentioned earlier, I've built an audience for distribution. A 1% conversion of my community would be about 60,000 units reach organically and theoretically without any ad spend. I'm Chef Reactions, a former chef, turned founder. Along with my marketing wizard, Mary, we're bringing you back-of-house Spice Company. Look forward to your questions.

SPEAKER_94: All right. Thanks, Chef. All right. We'll start with Stu. Question for Chef.

SPEAKER_75: Really great and cool to hear kind of more of the background. Do you worry that the long shelf life, it's an advantage in some ways, but do you also worry that that prevents you from getting recurring customers, recurring revenue because especially if you're selling to consumers, maybe they're not going through the spices as quickly, and they do stay good for a long time.

SPEAKER_78: All right. Thanks. And how about you, Gary?

SPEAKER_04: Yeah. Maybe if you could talk a little bit about the competition and distribution.

SPEAKER_33: So I know you have the audience, but how are you actually trying to move the product generally?

SPEAKER_117: Sure. Stu, thanks for your question. With regards to shelf life, it is a bit of a double-edged sword, admittedly.

SPEAKER_106: We want a product that's going to last, obviously. We want a high-quality product that's going to have a shelf life. With the staple products such as the salt and the pepper blend, those are going to be constantly renewed, hopefully, items that people use in literally every recipe. Also, we're going to really encourage people to use the spices through content, competitions, contests, things like that, and really engage the audience to use the spices and buy some more after they use them. Gary, with regards to the competition, I like to use Liquid Death as an example. As a company that sells a fairly ubiquitous product, water being the most ubiquitous product on the planet, we're really going to use our brand to stand out and use, as I said, the audience that I've kind of built up to build a sense of community. And we're going to do that through direct-to-consumer strictly to start with. And then, hopefully, maybe we'll move into retail one day, wholesale restaurant supply and stuff like that.

SPEAKER_122: I would be remiss if I didn't interject and say that I'm a huge fan. Oh, thank you very much. I really appreciate it. That's all we are. Thank you.

SPEAKER_88: Yeah, we have a theory that most people cannot make CPG work, but the people who can, can really build a billion-dollar business. And Mr. Beast, our friends at Science, Peter Pham and Mike Jones, we're partners with them on Real Boss Sour. We co-led the seed with them. And watching Chef, we realized the authenticity, the billions of views, the millions of listeners, takes what was the worst part of the tech CPG challenge out of the picture, which is getting the first 10,000 customers, the first 100,000 customers. It's kind of baked in with Chefs. And you can see that in the partners, like Thermador, the famous, what's the famous apron company that's on? Hedley and Bennett. The bear. Hedley and Bennett. Like, he has the equivalent of the Mercedes-Benz and the Hermes of his field obsessed with him. And when he came to our Liquidity Angel Summit event up in Napa, he had to excuse himself from the poker game. And he's like, I can't make it. I'm really sorry. Because I have to go to French Laundry, where they literally are so obsessed with him that they made a menu for him. And, you know, just knocked his socks off. And then when the check came, it just said, your money is no good here. So, you know, influences, you know, authentic relationships over influence. This word influence has got kind of icky, right? I think there's authentic connection that occurs with certain, you know, folks. And, you know, Chef, I've just learned a lot from him as a content creator myself, which is he actually has a fundamental operating system and a rule set heuristics that he, you know, has really been thoughtful about creating for his content. What he does is elegantly simple, yet very complex. And then what he doesn't do is also, you know, the most important part of the puzzle. And so he's the next Anthony Bourdain in my mind. And, you know, he's like that heir apparent. And then people say that in the comments, like, I trust Chef when he says something. And it's always his reaction is always the first reaction. He doesn't, you know, pre do it. So you get this like level of authenticity that Gordon Ramsay stole from him and started trying to copy. And then when Gordon Ramsay stole

SPEAKER_86: his format, everybody was like, Gordon, not cool. You know, like you stole Chef's format.

SPEAKER_106: I, sorry to interrupt you, Jason. I think, I think Gordon did it before me. I know I do it better,

SPEAKER_132: but I think Gordon did it before me. I refuse. I refuse. It doesn't fit my narrative as an investor. Sorry. I'm talking my book here. Just, just to add on with the term influence,

SPEAKER_106: one thing that I've, I've really, I kind of scoffed at it before I got into this field, but the word community really comes to, comes to mind because I feel like I've really cultivated a community of, of, of people versus just followers or subscribers or whatever. I do feel that there's a true element of community there. And thank you, Jason, for your kind words.

SPEAKER_88: And then there's like, you know, you do pick things up in this very entertaining format, um, which, you know, the, the architecture of all in and this week in startups has always been laugh and learn has been my architecture. And, and I think chef has that same concept because he will say something very subtle, like wet hand, dry hand, wet hand, dry hand. And I was like, I I've never heard of that. I look it up. Oh, this is how you make bread and cutlets. If you're going to make, you know, uh, a chicken parm, you, you know, it's, you use the wet hand, the dry hand, it's super smart. Right. And then like cutting boards and just this little knowledge is embedded in there and it really is addicting. So great job. And, uh, we're really excited. And this is a, another situation where, by the way, um, we have two parts of our funnel now, um, that, um, have really given us a significant advantage and, and y'all are part of it with follow through partnerships. We find the companies, they listen to the pods, they come to founder university, which chef came to, I asked them to come and we put just a 25 K investment in to start because a lot of folks are afraid to write the 25 K check in our industry and be the first money in because it seems kind of crazy to LP is like, why are you doing that? The reason we're doing it is it sometimes can be the difference between somebody starting a company and not. Um, and in this case it might've been, um, and then, you know, chef made such great progress in the first year, doubling or tripling the influencer revenue that I said, Hey, what's next? He showed me this idea. And then we put the one 25 in and worked with him for another 14 weeks. So we've got now 28 weeks of working with chef. And that's really the magic of the program. Now is founder university gets people off the bench, two or three person teams, 250 teams. We put 25 K into maybe 25 of them, each class. Then if folks want the 125 K check, yeah, come to the accelerator. So, and then y'all are part of like putting the seed round together in, in this formula. So we appreciate you making those 250 K 500 K checks, uh, and maybe helping us lead these and then getting them ready for the series. All right. Let's keep going. Next up,

SPEAKER_140: we have Vinay who is ahead of me. Layer path. Can we hear you Vinay? Hey, can you hear me? Okay. Yeah, sure. I can. I'm going to count you in three, two, go. Hey everyone. I'm Vinay,

SPEAKER_141: founder and CEO at layer path at layer path. We help teams create AI power training and onboarding content in minutes, not weeks. Why do we do this? I've spent over a decade in enterprise SaaS and I've worked with companies who have grown their user base from thousands to millions. And one thing always persisted. How do you effectively communicate the value of your product to your employees and your users? Um, and it's not just the enterprise SaaS problem. It's across the board of all enterprises across all sectors, because even in 2024, creating a training content is super hard. Meet Daniel, customer success manager at Turbox. Let's see how Daniel uses layer path to create a quick training content using layer path. This is Daniel's HubSpot CRM instance, and he wants to quickly create content to explain how the privacy feature in HubSpot works. He uses Chrome plugin, goes through every actions that he wants to capture and the layer path automatically captures his intent, his actions and produces content into three different format tour guide and video all in less than 30 seconds. He can then continue picking the type of format he wants, continue editing it using AI. He can work with 15 different languages to give content in the language that is most preferred for his customers or employees. And to share, he can either share a link, embed it on his help documents, or create a studio quality video with 4K resolutions, automatic voiceovers. And it's not just that, he can also see how his clients and employees are engaging with his content. Layer path has been transformative for Daniel. You know, he's cut down his content creation by 80% while still giving him the multi-format content which wasn't available before. Since the launch in Feb 2024, we've organically grown to 5,000 plus signups with 1300 paid beta users and 20 teams on subscription. We've also been fortunate enough to get into mid-market customers in the last two months. And the growth and adoption of a product continues to rise, showing a significant demand in people wanting a tool like layer path. Today, we are self-serve and PLG for SMBs and startups. And since we have got some traction in the mid-market, we want to focus on enterprises with multi-year contracts starting at $5,000 a year. Layer path distinguishes itself from the huge crowded market because we are the first, at least the first to step in with multi-model content creation. And that becomes our technical wedge. And also the demand for the market continues to grow with the recent acquisition of WalkMe by SAP in June 2024, sending shockwaves at the industry. And the market demand continues to grow even with all the AI hype out there. Our goal for $100 million start with video crafted for training and onboarding, move into redefining how knowledge bases and learning management systems are built, and then hit the digital adoption market with our aim to get into $100 million. And to do that, we are focusing on two things. One, product-led self-serve, which we are already doing. And my background is partner-led in the last 10 years at Zoho. And the focus would be more to get into channel partnerships and enterprises. We are the team to create it because our founding team comes from having gone through the challenge, creating those technical documentation, and also designing the videos. That's Layer Path. We help teams streamline their training and onboarding content

SPEAKER_54: in minutes. Thank you. All right. Thanks, Vinay. So Katie, we'll come to you next. Question for Vinay.

SPEAKER_10: Yeah, again, an ongoing theme of go-to-market. So this is an area that I've seen actually a lot of companies try to do, and how do you argue to your buyer that this is a must-have?

SPEAKER_12: All right. Thanks, Katie. Sandy? Maybe double-clicking on go-to-market. I think you said that ACV is 5K, which makes it tough to incentivize outbound sales at that ACV. I think you mentioned channel partnerships, but maybe you can double-click on go-to-market. Great questions. Yeah. Both in the GTM,

SPEAKER_141: which allow. To start with Katie's question, it's a new category that we are into, the interactive demo, then tapping into the distiller option. We've been doing a lot of educational-driven. You know, there is no direct demand. At least four years ago, there was no direct demand. We need to latch into existing categories. So the focus on making it must-have is to first show the people that the solution exists. So we've been perfecting our inbound content marketing over the last six months, really looking at how people are searching. You know, even if there is no direct demand, you can always, you know, include alternative demand. And that's something that I specialize. There is a need for this. It's just that people are not aware. So that because a new category is being created post the pandemic. And to touch on Sandy's question, I think the best way to move forward for us is a hybrid model of inbound and outbound. And that is something we learned from while securing two mid-market deals. They came through our content, signed up, set up a demo. And when you spend time with them, this was just the cycle of the sales was less than 48 hours. You show them the value and how they can onboard their teams. And the closing of deals was great. So now we know what a mid-market and enterprises are looking for. We want to understand these needs and then move into channel and the ISV partner integration, which is where. White label is also one of the things we're exploring. And we have one of our white label partners who's doing this for commercial real estate, which is a huge category, which I have no clue about. And we have a very targeted revenue to drive through this partnership of 10K in two months. So that's also a channel that we're continuing to invest and explore. I hope that answered your question. Thank you.

SPEAKER_00: All right. Thanks, Fanae. And founders, reminder to please check the Q&A box. Is there questions in there? Okay, Rafa. Masoud, can you hear us? Can we hear you more importantly? Yep. Hello, hello.

Chamath Palihapitiya: Three, two, go. Hey, everyone. I'm Masoud, one of the founders of Rafa, and we're going after LinkedIn's lunch money. In order to do that, we started our beachhead. We built a contextual recruiting platform that understands context and captures culture, fit, and hard skills from applicants without conducting a phone screen. Let's take a look at Tejas, for example. He's the founder of Dementia.dev. He raised a couple million bucks, so you already know what that means he needed to hire. And just like every founder that's on this panel and in your portfolio decided to pull software off the shelf, in this case, being Ashby, he posted two jobs and ran into the qualifying problem. He received over thousands of applications between inbound and outbound. His team was pulled away from what they do best, which is building, ended up reviewing the wrong resume, scheduling the wrong call, and meeting the wrong person just to have a less than 2% passing rate. So he decided to make a change and use Rafa instead. Let me show how it works. So when he creates a job, he's able to add the burning questions up front. In this case, why do you want to work at Dementia.dev? He can also ask technical, behavioral. Candidate discovers it via their career page or job board, and then for the very first time is able to go above and beyond the LinkedIn's and the resumes and speak to their merits. And since hiring is a team sport, his team of 10 was able to build consensus at step zero, reviewing and listening to the transcript and summaries. And the result, they were able to decrease spam applications by 98%, increase the passive rate by 50%, they skipped the first and second call, and were able to save 60 hours a week. The 100 billion data mode that's being formed in front of you is a contextual recruiting network that is able to index every working professional story and get them connected with opportunities better than LinkedIn or any other of the bigger players. Tages is not the only one though. We launched our public beta February. We're doing over 6k MRR, 200 companies on trial. We've been growing 35% month over month. We actually onboarded Fortune 10 and Fortune 50 enterprise companies on pilot. We've conducted over 10,000 phone screens, transcribed over 20,000 minutes of audio, and created over 600, 800 plus jobs. ICP, startups, agency recruiters. This is for Katie. We also, as you can see, going for enterprise. Initial GTM motion has been good old ice cold outbound, just the way I like it. And also founder led marketing, led by me. The way we make money now and the way we make more money later is 200 bucks a month, $10 per seat. Enterprise would be paying us $2,000 a month per seat to access our sourcing capabilities. And yes, your AI agent and AI recruiter will be sourcing on top of us and paying us instead of LinkedIn. LinkedIn is a one dimensional company. Rafa is a three dimensional company. Instead of paying $20,000 for a LinkedIn recruiter seat, you're paying a fraction of the cost and getting more results. We've been building products for over 40 plus years. I was a design lead at Meta, Moonlighter recruiter for eight plus years. So I've seen the good, the bad, and the ugly. My counterpart, Marcel tech lead at Cloud Kitchen Salesforce, Yahoo, and Amazon. He got all the logos. And that's us. Happy to answer your questions.

SPEAKER_90: All right. Thanks, Massoud. Stu, you're up. Question for Massoud.

SPEAKER_19: Really cool. Really interesting. Very, very busy space. How do you differentiate?

SPEAKER_49: All right. And back around to you, Gary.

SPEAKER_162: I'm sorry if I miss this, but are you selling, is it B2C and B2B on the sales flow? So maybe you can just explain that piece to me. Okay. Two minutes and soon.

Chamath Palihapitiya: Sure. Real quick, Gary, since this is a pretty fast one, it's been BDB. So startups, agency, agency recruiters, as well as enterprise, they've been finding us through inbound and outbound channels. So as you can see, like if you go on our, funny enough, LinkedIn, Twitter, or anywhere else, I'm always selling. And that's usually how people find us. So just like to nip that in. And as for Stu, when it comes to this space, you're seeing a lot of AI recruiters coming out. You're seeing a lot of noise. To kind of educate everyone, hiring and recruiting tools were actually pretty bad before AI. The human processes were actually way more distant as it should be. And with the introduction of AI, all of a sudden recruiting has become only transactional and the person's sentiment stories or what makes this process good, which is a human element has been disappearing. And so the way we win here is just by candidate experience. We get candidates day in, day out, DM us, emailing us, and we even have customers saying that in the first 10 seconds of the audio recording to our interview question, they're saying, thank you for giving me the platform to tell my story. And on top of that, since recruiting is becoming transactional in the AI world, candidates will want to use our platform. Companies will want to use our platform because your brand becomes everything. Your recruiting process is a window into how you manage your company. And so companies have been loving us and that's kind of like how we win here is having a good candidate experience, having a good company experience. And on top of that, we create our own data set. You remove the mask for every AI recruiter. It's going to be web crawlers, web scrapers and LinkedIn and old stale resumes from LinkedIn. So yeah. All right. Thanks Rafa. Just in time. Also,

SPEAKER_172: you have another question from Katie in the chat. If you can go ahead and answer that in the chat, that'd be great. All right. That's our cohort. That's LA 32. Now investors, here comes the hard part for you. I am going to ask you to give us your top three of those strong seven that you saw, and typically through the lens of investment. But I think if you just really like a company, you think it'd get really big, feel free to send them a vote. So I'm going to ask you to give us your top three in backwards order when I call on you. And you can just say the name of the company for three and two. My number three is this company. My number two is that company. But when you tell us your number one, maybe say a few words about why you voted that number one. We'll let you think about that. In the meantime, syndicate members would love for you to take our poll. So we're going to launch a poll and our guest investor judges don't look at that poll or be influenced by syndicate numbers,

SPEAKER_00: please. We'll keep these separate as much as we can. So yeah, your top, we can't do top three, but your top, please go ahead and vote for your top. And we will keep that going. I'll do a quick

SPEAKER_172: recap of the companies. You saw MasterTech, AI co-pilot for Automative Repair. Quirio enables

SPEAKER_00: companies to do analysis and reporting on data at any technical level. Convertmate, using AI to automate SEO for e-commerce. Ellis, outbound sales platform for startups. Layerpath, using AI to help companies create interactive product demos and studio quality explainer videos. And Rafa, applicant training system that captures culture fit and hard skills from applicants without picking up the phone. Contextual recruiting. Okay. I think I've hopefully filibustered long enough. Our

SPEAKER_172: guest investor judges, I'm going to start calling on you for your top three. We'll do this. And again, in backwards order, we'll do this first name alphabetical as I did the question. So Gary, we'll start with you. Top three in backwards order.

SPEAKER_162: All right. So my number three is Chef. My number two is Ellis. And my number one is MasterTech. And the reason I wanted, or put MasterTech as number one, it's probably the closest aligned to my thesis, maybe one of two. And I just love the pitch. Thought Linda did a great job and curious to learn more.

SPEAKER_10: All right. Thanks, Gary. Katie? Amazing cohort. And this is super hard. Number three is Rafa. Number two is MasterTech. And number one is Chef. And literally, I'm not kidding. I'm in a hotel room and I have these spices. I don't know if you can see it, but I like when I travel. This isn't even part of our Moxie thesis, but just, I felt this strong leaning towards what Chef is doing. I love the storytelling. I love the brand. I just love the founder market fit. So really fired up. Thanks, Katie. Sandy?

SPEAKER_12: And number three was MasterTech. Number two, Querio. And number one was Chef. I just think it's a great category to be going after kind of, you know, a lot of old tired brands there. I imagine the unit economics are pretty strong. It's also easy to ship through the mail. And yeah, you have an audience. And like, that's the biggest thing that matters with direct-to-consumer these days. So yeah, I'm a fan. Thanks, Andy. Stu?

SPEAKER_74: Congrats, everyone. Really awesome job. My number three is Chef. Number two is MasterTech. Number one is

SPEAKER_75: Ellis. I think the idea of combining CRM with outreach, with the customer data. If what you're saying this is going to be is actually going to work for customers, I think it could be pretty huge.

SPEAKER_172: All right. Okay, great. So Andre, we're going to do three things here. First, we're going to, what is our score today with our judges, and then the poll, and then the overall score. We do this week to week, and we give the overall winners. So Andre, what was today's score?

SPEAKER_191: All right. Thanks everyone for voting. So today with, in third place, three points is Ellis. In second place with 4.5 points is MasterTech. And with five points in first is Chef Reactions. Okay. And for our syndicate poll? And for our syndicate poll, looks like overall with 37% of the votes is MasterTech. And first. And then second in, I'll go first, second, third. Second,

SPEAKER_193: Queryo with 19%, and then Chef with 14%. Okay. And overall for the cohort, three, two, one.

SPEAKER_191: All right. So across all the sessions that we've had, Ellis is in third overall, Queryo is in second, and first is MasterTech. Well done founders. Any last words, Jason? Thanks

SPEAKER_124: everyone for joining us. Well, it's all about community. And what you'll see from our accelerator

SPEAKER_88: is the result of 20,000 applications resulting in 4,000 phone calls that our 21 person team does. We take those 4,000 calls or 5,000 calls we do a year. And we have about 1,000 people go to Foundry University, and then we'll have about 30 people come to the accelerator of the 1,000 who go to Foundry University. We'll put 25K checks into 50 to 75 of those. So you all get to benefit from our filtering process. And then you get to do your filter on top of this insane filter that we're doing. And it takes a ton of work. So I want to say thank you to our team. Andre is now going to be running the accelerator after Jackie did it. Jackie's working on LP relationships in our Whisper network. Our Whisper network is a secret program where we will tell some of our trusted partners in advance of a demo day, here's a couple of companies we think are in your zone. So we have a program and a database of our top, I think it's about 200 firms, seed funds, series A funds, and then maybe four partners at each. So about 800 individuals in our Whisper network who we've developed relationships with, like Stu and Katie and folks who are on the call here, who will just whisper, hey, they're not necessarily raising money, but this company is starting to get a little bit of product market fit, et cetera. And then people tell us, hey, thanks so much, Jackie. We're not into marketplaces, and we don't do consumer. We're really enterprise and security. So great. We note that in our database, we don't waste our time in the future. And so if you want to update your profile in the Whisper network with Jackie, she can do that with you. And so you let us know where you like the ball and we will pass you the ball exactly where you like it for a slam dunk or a three point or whatever your reference is. Congrats to the companies, product, team, customer, just focus on those three things and your chances of building an important company go way up and block out everything else. We'll see y'all next time. Bye-bye.