 Good evening, everyone. Welcome back to theCUBE's live coverage, day one, Snowflake Summit 2023, from Caesar's Forum in Las Vegas. It's happy hour, it's happy hour in Las Vegas. It's been happy hour for a couple of hours. But Dave and I are here. We're having some amazing conversations today. Up next, a conversation with the co-founder and CEO of AirBite. We're going to be talking about open source data integration. No Dave, a lot of supported connectors from any one vendor has typically plateaued out around 150 until now. And we're going to be talking about AirBite. I didn't know that stat. Yes, please welcome Michelle Trico, co-founder and CEO of AirBite. Michelle, welcome to theCUBE. Thank you for having me. Tell us a little bit about AirBite, the catalyst to launch the company, what it is that you do for your customers. Yeah, so I've been working in the data space for the past 15 years. And every time I've been working on data, I've noticed that teams always do the same thing, which is, and they always have the same problem, which is how do I access data across all the systems that I have, whether it's a Salesforce silo, a HubSpot silo, a Google ad silo, a database, et cetera. And every team is redoing the same thing over and over again, which is building a connector, pulling data out of the system and centralizing that data somewhere. And with modern warehouses like Snowflake, that has become even more of a need for companies. And early 2020 with my co-founder, we started AirBite. And our mission was really how do we address the long tail of data connectors? So not just the top 20 that everybody has, it's also all these other places, all these other connectors. And we decided to go for something open source so that people can one build their own connectors, maintain connectors, but also and grow that long tail very, very fast. As I mentioned in the intro, and as some of the research I was doing on AirBite, the number of supported connectors is typically plateaued out at 150 because the ROI isn't simply there to justify more. Why is AirBite different? How did you get past that plateau? Yeah, so we do it because we are not the only one maintaining connector. So we do a part of it, but then we work with our community. We work with our customers to actually share the load and the burden of this maintenance because the moment you start using a connector, you have an incentive to make sure that this connector always works. And that's the way of spreading the load and instead of having every single thing doing it, you just have one team that does it and suddenly the rest of the teams have access to the same quality of connectors and the same type of connectors. So connector creep kills you, right? Now, Michelle, this has been tried before, I think, and I think back to the big data days. I think of a company like Adapt. They were trying to sort of eliminate connectors. They didn't quite get it right. Now, maybe that was because it was Hadoop that killed them. I don't know, but so what's fast forward to 2020 when you started the company, what's changed? Yeah, so when you go back to the days of the Hadoop, the key way of accessing data was files. And people were just trying to dump as many files as possible and you did not really have that many places where a company had data. It was in general one or two main product databases, one ERP, a few APIs, but that's all. What you've seen over the past 10 years is people are using and consuming a lot of SaaS product. And you know, just a recent study so that we went from 16 on average to 130. So these are all 130 little silos of data and yeah, like the demand for that data is not coming from engineers anymore. When it was Hadoop, it was engineers, data engineers looking to get data somewhere. Now it comes from a marketing upstream, a sales upstreams, a finance upstreams and they need that data to do their job and they are asking for breaking down these silos. Can you paint a picture of the value chain because maybe starting with the business person, marketing team going through however they get the data, less and less it's dashboards, it's more answers. And then where you guys fit in that value chain. Yeah, so let's say you're a marketing obscurson to understand how your ID is performing, to understand how your email campaign is performing, to understand all of this. You basically need to connect to your ad platforms. You need to connect to your email provider. You need to connect to your marketing CRM. And this is where the needs come from. And then when you go look just at the data value chain, what's going to happen is that marketing obscurson is going to connect to our bytes and say, okay, push the data that is on my HubSpot instance and make it available in Snowflake. So that now I can connect, put my dashboard on it, put my automation on top of my Snowflake and start extracting this information so that my next campaign, my next ad campaign, my next email campaign is higher quality and I've learned from everything I've done in the past to do make the future better. Okay, and so you essentially enable that. And the value, how do you describe the value proposition from an economic standpoint? From, yeah, I mean, I think at that point it's really why do we have a RevOps or why do we have a sales upstream? Like these functions are here to build more operational efficiency within a sales team, for example. If you can bring the right data to the right salesperson while they are talking to a customer, then boom, they might close this customer faster or they might just close it plain and simple or they might be able to upsell that customer. If they realize that, oh, this customer is consuming 50% of all our customer success and our support time, maybe we need to upsell them something on support. So that becomes one of the value prop if you're looking at it from the lens of a sales upstream. You're accelerating the existing value proposition of a very important function of the company that's already been established and justified. Exactly. So it's kind of a no-brainer. What's your relationship with Snowflake? What's that partnership like? So the first thing when we released Airbuy the first time, Snowflake was the top places where people wanted to put data in. And we very quickly developed that ability to push data into Snowflake. And one of the things you get with open source is control, control over where your data is going and the way our connectors are working, they can run directly into Snowflake. So we have our own platform, which is a cloud product or we have our enterprise solution. But we also now have the ability to run Airbuy's connector directly into Snowflake native apps. And that's something we announced today where, yeah, if you don't want data to be accessed by anyone else than you and maybe Snowflake, this is something you can do. And open source give you that control because yeah, you can push that connector over there. Talk a little bit more about the native app that you just announced this morning. You mentioned some from a security perspective, but talk to us about some of the value drivers there and some of the outcomes that customers could expect to get from that. Yeah, I think the overall vision here is of adoption in a sense that once you're using Snowflake, you have a stamp around security, around your data. So if you can run most of your data processing within the Snowflake environment and that's the case for us, like we run data ingestion, then everything happens within the security of Snowflake. So I think even for us as vendors, it removes friction, meaning that if you're trying to sell your product and you get stuck at the security level, you don't have that problem anymore because now you're already vetted by the Snowflake secure environment. So that's a big advantage both for us as vendors but also for our customers because it speeds up adoptions of new tools. So you guys have raised, if CrunchBase is accurate, a fair amount of money. You've done an acquisition. So give us the highlight of the company where it's at. I think you're at Series B. Yeah, so yeah, we raised about 180 million and as I said before, we've been really focused on making AirBite as ubiquitous as possible, meaning the moment you need to bring data from one system to another system, AirBite should be top of mind and I think this is really what we've done over the past three years, which is being top of mind, a top of mind solution for everything data ingestion, ETL, ELT related. Now, our focus has really been on this top four product, open source. So very strong adoption, bottom up adoption and the first production pipeline goes through open source and then we focus on the rest of, as you might share with AirBite, is how do you, like what are the additional requirements that you have around like SSO, RBAC and that became our enterprise solution and where we provide support at that point. And after that cloud, you might not want to host AirBite yourself, you'll find using a SaaS service, good for you, we have a cloud product for you. And the last one was what we call Powered by AirBite, which is powering tools to bring more data into applications. And this has really been the, yeah, the accomplishment over the past three years is addressing these four different angles for making AirBite ubiquitous. So a lot of growth and acceleration in a very short time period, during a pandemic I might add, how have customers and the Snowflake partnership and their customer base influence this accelerated growth trajectory that you seem to be on? Yeah, I think what you see there is that every time there is a crisis, people are just going to dive down a little bit on growth and focus on fundamentals. And what has happened really during, and we've seen it firsthand during the pandemic, is people stop investing in some growth areas and they started to refocus on this long project that they know are necessary for the future, but that might not be the most, yeah. But growth might have taken all the resources at the time. And what we've seen during the pandemic is people really looked at their infrastructure and what do they need to bring to make, to prepare their companies and their organization for the future. So they use that calm, more calm time of COVID. I don't know if you can say it's calm, but it was a little bit quieter and they just made this investment. And for us that was a big accelerator because suddenly people are adopting solutions like Snowflake and the first question people ask themselves when they acquire Snowflake is, how do I bring data into Snowflake? And AirBike was there to help. Well, my last question for you is, did you happen to catch the keynote, the fireside chat last night between Frank and Jensen? I did, I saw the summary. One of the things that Jensen said, one of the many things Jensen said that was colorful and interesting was that, companies have to go from being data companies, software companies to AI factories. AI factory, how can the AirBike Snowflake partnership help customers become or generate AI factories so that they can be competitive, deliver new products and services and new apps to their customers? Yeah, it's funny because just before I was making, I was doing a talk and one of my statement was, today, whether you are in retail, whether you are in insurance, whether you're in banking, every single person, every single one of these companies is a data company. And I think it just talks to the foundation and the requirements that is necessary for companies. Like, every company must be good with data. And the reason why it's important is because now it enables these additional places where data has value and AI is a big one. When like you can have the best AI algorithm in the world, if you don't have data to power this algorithm, it's not going to be helpful, especially when you start working with large language model where you want to inject your own proprietary knowledge into the product. If you don't have that data, your LLM is not going to serve you well. And that's where this type of partnership becomes important because people that are using Snowflake are also really thinking hard about, how do I make AI part of my strategy? And we just want to continue to funnel more of that data to power not only analytics, not only like operational use cases, but really AI as a big one. Ah, excellent. Michelle, thank you so much for joining us, talking about AirBike. I see you now have 300 plus connectors available. So you really, we'll just wipe that plateau right off the table. We appreciate you coming on theCUBE, talking to us about AirBike, what you're doing with Snowflake. Thank you. Thank you for having me. Thanks, Michelle. We're our guests and Dave Vellante. I'm Lisa Martin. You've been watching theCUBE's day one coverage of Snowflake Summit. Tomorrow, this is a wrap for day one. Tomorrow, don't miss out. We have a great guest lineup all day tomorrow. Frank Slutman will be here in the morning doing a great one-on-one with Dave. We also want to remind you that you can find all of our Snowflake assets and all of theCUBE content on theCUBE.net and all of the great analysis on siliconangle.com. Thanks everyone so much for watching. Have a great day. We'll see you tomorrow.