>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

(upbeat music) >> Welcome to today's session of theCUBE's presentation of the AWS Startup Showcase, the Next Big Thing in AI, Security & Life Sciences. Today we're joined by Abacus Insights for the Life Sciences track, I'm your host, Natalie Ehrlich. Now we're going to be speaking about creating an innovation enabling data environment to accelerate your healthcare analytics journey, and we're now joined by our guests Krishna Kottapalli, chief commercial officer as well as Sumant Rao, chief product officer, both working at Abacus Insights, thank you very much for joining us. >> Thank you for having us. >> Well let's kick off with our theme Krishna, how can we create innovation enabling data environments in order to facilitate the healthcare analytics? >> Yeah, so I think if you sort of think about this that is a lot of data proliferating inside the healthcare system, and whether it's through the internal sources, external sources, devices, patient monitoring platforms, and so on, and all of this carries yeah all of these essentially carry, have useful data and intelligence, right, and essentially the users are looking to get insights out of it to solve problems. And we're also seeing that the journey that our clients are going through is actually a transformation journey, right so they are thinking about how do we seamlessly interact with our stakeholders, so their stakeholders being members and providers, so that they don't get frustrated and feel like they're interacting with multiple parts of the health plan, right, we typically when you call the health plan you feel like you're calling five different departments, so they want to have a seamless experience, and finally, I think the whole, you know, the data being you know, in the ecosystem within the patients, payers, and providers being able to operate and interact has intelligence. So what we, what we think about this is how do we take all of this and help our clients you know, digitize their, you know, path forward and create a way to deliver, you know enable them to do meaningful analytics. >> Well Sumant, when you think about your customers what are the key benefits that Abacus is providing? >> So that's a good question, so primarily speaking, we approach this as, you know a framework that drives innovation that enables data and analytics. I mean, that's really what we're trying to do here. What Abacus does though, is this is slightly different is how we think about this. So we firmly believe that data analytics is not a linear journey, I mean, you cannot say that, oh I'll build my data foundation first and then, you know have the data and then they shall come that's not how it works. So for us, the way Abacus approaches this is, we focus really heavily on the data foundation part of it first. But along the way in the process, a big part of our value statement is we engage and make sure we are driving business value throughout this piece. So, so general message is, you know make sure innovation for the sake of innovation data is not how you're approaching this, but think about your business users, get them engaged, have it small, milestone driven progress that you make along the way. So, so generally speaking, it's we're not tryna be just a platform who moves bits and bytes of information. The way we think about this is you know we'll help you along this journey, there are steps that happen that take you there. And because of which, the message to most of our customers is you focus on your core competence. You know your business, you have nuances in the data, you have nuances on needs that your customers need, you focus on that. The scale that Abacus brings because this is what we do day in day out is more along area of re-usability. So if within our customers, they've got data assets how do we reuse some of that? How does Abacus re-use the fact that because of our of what we do, we actually have data assets that, you know, we can bring data to life quickly. So, so general guidelines, right, so first is don't innovate for the sake of innovating. I mean, that's not going to get you far, respect the process that this is not a linear path, there's always value that's happening throughout the process, and that's, you know, Abacus will work closely with you to make sure you recognize that value. The second part is within your organization, you have assets. There's like major data assets, there's IP, there's things that can leverage that Abacus will do. And because we are a platform, what we focus on is configurability. We've done this for, I mean, a lot of us on the Abacus team come from healthcare space, we have got big payer DNA, we get this, and what we also know is data rules change. I mean, you know, it's really hard when you build a system that's tightly built and you cannot change and you cannot adapt as data rules change, so we've made that part of it easier. We have, we understand data governance, so we work closely with our payers data governance teams to make sure that part of it happens. And I think the last part of this which is really important, this in the context of this conversation is, all of this is good stuff, I mean, you've got massive data foundation, you've got, you know, healthcare expertise flowing in, you've got partnerships with data governance, all that is great. If you don't have best-in-class infrastructure supporting all of that, then you really, you will really have issues Erlich. I mean, that's just the way it works, and this is why, you know, we're built on the AWS stack which kind of helps us, and also helps our clients along with their cloud journey. So it's kind of an interesting set of events in terms of you know, again, I'm going to repeat this because it's important that we don't innovate for the sake of innovating, re-use your assets, leverage your existing IP, make things configurable, data changes, and then leverage best in class infrastructure, so Abacus strategy progresses across those four dimensions. >> And I mean, that's an excellent point about healthcare data being really nuanced and you know, Krishna would love to get your insights on what you see are the biggest opportunities in healthcare analytics now. >> Yeah, so the biggest opportunities are, you know there are two, we think about it in two dimensions, right, one is really around sort of the analytics use cases, and second is around the operational use cases, right, so if you think about a payer they're trying to solve both, and we see because of, you know, our the way we think about data, which is close to near real time, we are able to essentially serve up our clients with, you know helping them solve both their use cases. So think of this that, when you're a patient, you go to you know, you go to a CVS to do something, and then you go to your doctor's office to do something, right, to be, to be able to take a test. If all of these are known, to your payer care management team, if you will, in close to near real time then know, right, where you've been, what you can do how to be able to sort of intervene and so on and so forth, so from a next best action and operational use cases we see a lot of them emerging, new thanks to the cloud as well as thanks to infrastructure, which can do sort of near real time. So that's our own sort of operational use cases if you will. If, when you think about the analytics right, so, you know, every, all payers struggle with this, Which is you have limited dollars to be able to intervene with you know, a large set of population, right so every piece of data that you know, have about your patient, about the specific provider so on and so forth is able to actually, you know give you analytics to be able to intervene or engage if you will, with the patient in a very one-to-one manner. And what we find is at the end of the day if the patient is not engaged in this and the member or the patient is not engaged, you know in the healthcare, you know, value chain, if you will, then your dollars go to waste, and we feel that, in essentially both of these type of use cases can be sorted up really well with, with a unified data platform, as well as with upstack analytics. >> And now Sumant, I'd love to hear from you, you know you're really involved with the product, how do you see the competitive landscape? How do you make sure that your product is the best out there? >> So I think, I think a lot of that is we think about ourselves across three, three vectors. Talk about it as core platform, which is at a very minimal level of description, it's really moving bits and bytes from point A to point B. That's one part of it, right, and I think there's a, it's a pretty crowded space, it's a whole bunch of folks out there trying to, you know demonstrate that they can successfully land data from one point to the other. We do that too, we do that at scale. Where you'd start differentiating and pulling away from the pack is the second vector, which is enrichment. Now, this is where again, it's you have to understand healthcare data to really build a level of respect for how messy it can get. And you have to understand it and build it in a way where it's easy to keep up with the changes. We spend a lot of time, you know in building out a platform to do that so that we can implement data quickly. I mean, you know, for Abacus to bring a data source to life in less than 45 days, it's pretty straightforward. And it's you're talking on an average 6 or 12 months across the rest. Because we get this, we've got a library of rules, we understand how to bring this piece, so we start pulling away from the competitors, if you may. More along the enrichment vector, because that's where we think, getting high quality rules, getting these re-used, all of this is part of it, but then we bring another level of enrichment where we have, you know, we use public data sets, we use a reference data sets, we tie this, we fill in the blanks in the data. All of this is the end state, let's make the data shovel-ready for analytics. So we do all of that along the way, so now applying our expertise, cleansing data, making sure it's the gaps are all filled out and getting this ready and then comes the next part where we tie this data out. Cause it's one thing to bring in multiple sources quickly at scale high speed and all that good stuff, which is hard work, but you know, it's, it's expected now at the same time how do you put all that together in a meaningful manner with which we can actually, you know, land it and keep it ready? So that's two parts. So first is, the platform, the nuts and bolts, the pipes, all that is good stuff, the second is the enrichment. The third side, which is really where we start differentiating is distribution. We have a philosophy that, you know, really the mission of the whole company was to get data available. To solve use cases like the one Krishna just talked about. So rather than make this a massive change management program that takes five years to implement, and really scares your end users away, our philosophy is like let's have incremental use case all on the way, but let's talk to the users, let them interact with data as easy as they can. So we've built our partnerships on our distribution hub, which makes it easy, so an example is if you have someone in the marketing team, who really wants to analyze a particular population to reach out to them, and all they know is tableau, it is great. It should be as simple as saying, look what's the sliver of data you need to get your job done, how do you interact? So we've our distribution hub, is really is the part where, users come in, interact with the data with you know, we will meet you where you are is the underlying principle and that's how it operates. So, so I think on the first level of platform, yeah a crowded space everyone's fighting for that piece, the second part of it is enrichment where we really start pulling away using our expertise, and then at the end of it you've got the distribution part where you know you just want to make it available to users, and, you know, a lot of work has gone into getting this done but that's how we work. >> And if I could add a couple more things, Natalie, so the other thing is security, right so the reason that healthcare, healthcare players have not gone to the cloud until about three four years back, is the whole concern about security so we have invested a ton of resources and money to make sure that our platform is run in the most secure manner, and giving confidence to our clients, and it's an expensive process, right, even though you're on AWS you have to have your own certification that, so that that gives us a huge differentiator, and the last but not least is how we actually approach the whole data management deployment process, which is, our clients think about us in two dimensions, total cost of ownership, but typically 50 to 60% of what it would cost internally, and secondly, time to value, right, you can't have an infinitely long deployment cycle. So we think about those two and actually put our skin in the game and tie our, you know, tie our success to total cost of ownership and time to value. >> Well, just really quick in 1-2 sentences, would love to get your insight on Abacus's defining contribution to the future of cloud scale. >> Go ahead, Sumant. >> So as I see it, I think so part of it is we've got some of our clients who are payers and we've got them along their cloud journey trusting one of their key assets which is data, and letting us drive it. And this is really driven by domain expertise, a good understanding of data governance, and a great understanding of security, I mean, combining all of this, we've actually got our clients sitting and operating on, you know pretty significant cloud infrastructure successfully day in day out. So I think we've done our part as far as, you know helping folks along that journey. >> Yeah and just to close it out I would say it is speed, right, it is speed to deployment, you don't have to wait. You know, we have set up the infrastructure, set up the cloud and the ability to get things up and running is literally we think about it in weeks, and not months. >> Terrific, well, thank you both very much for insights, fantastic to have you on the show, really fascinating to hear about how Abacus is leveraging healthcare data expertise on its platform , to drive robust analytics, and of course, here we were joined by Abacus Insights, Krishna Kottapalli, the chief commercial officer, as well as Sumant Rao, the chief product officer, thank you again very much for your insights on this program and this session of the AWS Startup Showcase. (upbeat music)

>> Narrator: From theCUBE studios in Palo Alto in Boston, connecting with all leaders all around the world, this is theCUBE conversation. >> Hi, everybody, this is Dave Vellante, and welcome to this episode of Startup Insights. Andrew Lau is here with me, he's the co founder and CEO of a relatively new company called Jellyfish. They focus on engineering management, which is kind of a new space that we want to present to you, Andrew, great to see you, thanks for coming on. >> Hey, Dave, thanks for having me on. >> So when I see co founder and a title I always ask why did you start a company? What's your Why? >> So the three co founders myself, Dave Gourley, and Phil Braden,we actually met geez more than 20 years ago, at a company called Endeca. We had the chance to kind of bring the proverbial band back together, just 'cause rare is the chance to work with great people. And for us, Jellyfish really was coming out of our own experiences. All three of us grew our careers running big engineering teams big product teams. We realized how hard it was to really lead those teams and connect them to the business at scale. And that's the problem we just got together to solve. >> Yeah, so interesting right, and Endeca, another East Coast company, great exit, brought by Oracle. And of course, when you say in Endeca, I always think okay, Jellyfish, you guys in the search business, but you're not in engineering management. What is engineering management? And, you know, how does it relate to some of your past experiences? >> Great question, well, so engineering management engineering management sector or management platform, as we talked about, really comes down to how we can facilitate the tools to make leading big teams easier, right, we've realized that as you get to larger teams, teams bigger than 50, bigger than 100 engineers, it's really hard to understand what the team is doing really hard to make sure that they're working their best in making sure they're pointed in the right direction. And even Furthermore, how to connect that to the business and how to make sure the business successful after the team dies. And as for us, is really around making tools and processes available that they really help accelerate the act of leading big teams. >> So when you think about it, I mean, it's really the problem you're solving is visibility, kind of what's going on in engineering and providing metrics is that a sort of a fair, high level? >> I think it's a perfect high level statement. When we actually got together and talked about the problem space we all saw as we lead these big teams. We quickly drew an analogy to you know, when I started my career in the late 90s, there was a time before Salesforce and CRM were pervasive, right And so really quickly, we drew a quick and easy analogy that said, like, hey, why isn't there a Salesforce for engineering? That is, why isn't it that same leadership and executive visibility into how a team is progressing and to make sure it's aligned with the business? >> Well, when you think about it, right, Salesforce, what 1999 we had the first Salesforce clouding before the real cloud hit, you know, we certainly have marketing clouds now capital Management clouds, customer service management clouds, why not an engineering cloud right? >> I think it's probably you follow that map there, I think we've seen the last 20 years, that clouds actually kind of progressed from sales to marketing to success to HR, as you pointed out, I think the last bastion in organizations is the engineering team right? It just so happens right now that engineering teams probably are the most strategic, if not the most expensive team in most companies roster. And so really, providing visibility is really necessary at this time. >> So I don't run engineering it's Silicon Angle by my co-CEO and partner John furrier does. But I'm always like asking him like, hey, what are you guys working on? What are the deliverables? What am I going to get it and when? how we do it on quality, and so forth and so I think just scanning your website, reading some of your blogs, these are some of the things that you really focus on. You wrote a five part series, I think, I don't know if I'm dying to see part five but four parts are out. I want to dig into some of those, I think they're in, I think you called it, you know, five things that you should present to the board. >> Yeah, yeah Like, you know, a great question around like, there's a series were four or five in two, I'm talking about what are five slides that heads of engineering should be showing to their boards or even their executive management teams? You know, early on in the process, I'm aware, before we actually started the company, we did a ton of research, talking with leaders at scale, trying to ask them, like, how do you manage your team? How do you connect into the business? And out of those conversations fell, you know, asking folks like, well, what slides do you show your board meeting? And and the answer was, there wasn't ubiquitous answer. People were looking for answers and so we really synthesized a number of different leaders that we thought were really successful in this world, and really put together this series to talk about like, what are the metrics that people should be measuring? >> Well, let's talk more about some of those metrics so you know, I mentioned so what am I going to get? When what are some of the other key things that people are focused on? I mean, obviously, quality, where I'm spending my money. But what are some of the ones that you're seeing, aligning with business and really driving business outcomes? >> So okay, so part one I think you talked about right which is, you know, what are you getting? What got shipped out the door? what's coming down the pipe? I think job one for a leader of engineering and Product is to talk about what's coming out, right in the same way that sales job is actually hit a revenue number and talk about the pipeline coming down the way it's an engineers job to actually ship new product that you can sell your users can engage with so that's definitely slide one. Slide two, you already alluded to here two is about quality, right? I think if you're shipping product that actually can't hold quality in the eyes of your customers, it won't last very long. So I think it's really important to show command of quality and actually show metrics that actually measure quality over time in the lens of your customer. Slide three, I think we're really talking about alignment. Making sure that your team is spending your dollars, time and effort in the right way that actually aligns with what the business wants to right? So examples might be, if you're a company that splits time between enterprise and SMB efforts, well, making sure that the features the team is working on actually aligned to the strategy of the company, right? And you can't do that if you don't measure that. And then slide four is really around capturing broad level productivity. But is the team healthy moving forward? And then the last of which is really the preview coming up for the next segment here is going to be about really around the team in hiring right. How is the team holding up? How's the morale? And how's the actual hiring pipeline looking and ramp? All right in terms of new employees right, it's really the people side of the engineering leadership. >> Cool, thanks for teasing that a little bit. I'm glad to hear it's not just about productivity, 'cause there are tools out there that can measure developer productivity, but seems like you're taking a broader approach and building a platform to really take a more end to end sort of lifecycle view. >> Yeah, I think we really look about, think about it as look productive is really important. I think it's necessary but not sufficient. You can talk about a boat, you can roll faster. But if you're rolling the boat in the wrong direction, who cares? So it's as important to make sure that alignments in place and actually making sure that the rest of communication and context is really in place to make sure that team succeeds and the lens of the business. >> Andrew I'm interested in the market, I mean, my sense is engineering management is sort of new, very new, actually, although we talked about productivity being sort of one of the metrics and there are tools out there, but how do you look at this market? Is there a big whale that you're targeting? Or is this more of a Greenfield up? >> I think really, it's a Greenfield opportunity. I think if you were to you know, people don't wake up right now with a quadrant they look at or a wave that they're actually measuring on at the moment. It doesn't say isn't coming. I mean, if you look at this as a baseball game, we're probably getting one and defining market right now. And you can tell because if you look across the vendor space, I think there's a lot of variety of different solutions in these places. And so, from my view, you know, there's room right now just to innovate and describe what this platform really is going to be right and that's what the next few years are going to look like and defining this market. >> Did the unknown nature of the market? Was that was that a challenge in terms of your race? >> I actually think that's actually the opportunity. I think both as founders and and our investors, I think really, whenever you have these Greenfield opportunities, it helps you create big opportunities, I either grow you know, this better than anyone, I think, define the markets are very clear in the box you're trying to fill in, it's a race to do that. You know, this space here is a space ripe for innovation. It needs innovation, both in product and process and how you going to market and the story will be told five years from now. >> So I want to talk about your go to market but before we do, so one of the things you got to do when you're doing your investor pitches, you got to figure out the total available market your served market. I mean, how did you do that? What can you share with us about the TAM? >> I mean, okay, there's the quantitative answer, right, you could pick apart all the companies in the world count all the software engineers and I can tell you, it's going to be a big number, right You can also map it to other large software engineering companies like Atlassian, or even Microsoft and talk about the markets there. But I think, you know, look, the world has moved far for long with that like, what's the word every company is a software company now? I think it's not a necessary part of the pitch anymore. I think everyone intuits the TAM is large, because even air conditioning companies now have hundreds of software engineers, It's no longer this niche thing like it was 20 years ago. I think literally, you know, every company in the planet could be a potential customer of Jellyfish in the future. >> You know I feel like some sometimes if you can actually size the TAM, it's maybe a negative in your race because if the TAM is just so obviously large then investors say hey, okay, check the markets huge, and that's what they want to see. >> And I think part of it too, is like we've seen the last five years, not just has you know, every company become a software company. This also means the engineering departments and how they recruit have been really scrutinized. Everybody needs more wants more engineers, they're hard to get and expensive. I think everyone's realizing like, because of both of those things, everyone cares a lot more, It's no longer this, you know, small number of people have low cost. It's actually just an expensive investment, a strategic one. And I want to make sure everyone wants to make sure it's pointing in the right direction now. >> So there's a lot of people in our community, young people get, you know, either just graduated from college or been out for, you know, 567 years working at a company and feel like they want to do their own thing. And they're always interested in how you did it, how you got started, how you ascended the company where you know how you seated it, I think, I think you guys started in 2017, I think you've raised $12 million. But take us back to the beginning, how did you and your co founders get launched, you know, how did you see the company and bootstrap it? So I mean, I, I think for us, like we're lucky to have actually been through all three of us through a number of different startups. So I think this is for us coming with a lot of awareness of actually how to build the company, we had the chance, you know, in at the talent 2016 to actually get the proverbial band back together. We hadn't worked together in probably shy of 15 years. But I think we really respected the chance to do so. And so we got together and said, like, hey, let's see if there's an opportunity for us to do something together. And so that was a real journey, you know, we pushed through a number of different concepts, we largely fell into this one simply because of our backgrounds, right, it is an area that we actually bring some personal expertise to and our networks bring it that way, but also some passion around wanting to actually solve it. So I think it's probably at the end of 16 that we actually said, like, hey, this is a space we might be interested in. We actually spent I think the the first couple months of 17 just interviewing every VPE CTO CEO, exactly we could find I think we probably talked to north of 65 technology leaders in that time period. Largely just actually asked him like, hey, what do you think about this space, this idea? What do you do instead? In fact, tell me not to start the startup, I don't want to invest x years of my life to find out that there's a better solution out there. The part that was I think amazing was that everyone was interviews, everybody kind of stopped at the end of it and leaned in and said, "hey, can you do me a favor? Can you write up the, whatever your notes on this and just send me the actual answer? So at that moment, we knew that, you know, we didn't have the solution yet. But we knew there's pain out there an opportunity to actually solve something, we weren't the only ones that actually identified that. And so that became the mission, which is how do we make people in this seat? How do we make their lives better, right? And, you know, sliding forward that you know, concurrent with actually, the early checks coming in, we actually call those same folks back and said, hey, can we work with you to build the product? So from a philosophical standpoint, we really believe in actually building with our customers, right, and so, from the first moment, you know, pre product, you know, pre code, we sat down with those same people and said, hey, let's work with you. let's do things by hand, let's do with your data, just to make sure that we understand what we're building a use case that you care about. >> Okay, so you co-created really with the customers as you actually started generating revenue, kind of a sell design build model, is that right, or? >> Yeah, I want to think of a much more of a, as an alpha product development, right, I think, you know, our philosophy on that early on, let's say June of 17. It was, look, we'll do your manual, we'll do your board decks for you, we'll do your management team slides, we'll do your metrics will do your capitalization, right. We'll do whatever you need on a manual basis, as long as we can work with you and your data. And you know, because we always had an eye on building the platform there. And so behind the scenes, of course, we're automating all of this. But that helps make sure that the use cases that we're building for were things they actually needed, we're going to use. >> Did you find you had to leave a lot on the cutting room floor? In other words, a lot of times when you take that approach, and you kind of try to generate maybe early revenue from customers, you sometimes get sick, especially in the enterprise, you get sucked into specials and some of your custom work that might not scale across the the other organizations. You guys obviously experienced, was that something you guys put a lot of thought into and how did you manage that? >> Look, I don't think it's magic, I think we were aware. To your point we've done this a few times, so at least we knew the pitfalls, like yeah, so some stuff has been left on the cutting for in the sense that we probably, you know, pushed harder on areas that we push less on today. I don't think anything was abandoned. I think part of it is that, you know, there's two sides of it, right, which is, if you're able to think about where you want to go, which is building a platform, you can always take any engagement and trade it off and say like, hey, is this something we want to build? Does this make sense for actually leading us towards the long platform story? you don't have to do every opportunity that comes along. So I think you need to thread the needle and I should take advantage of working with customers, but also making sure you have an eye for where you're going the North star so you can pick and choose which project you want to work on or which customers you know you want to work with because end of the day products are really the byproduct of who you work for who you serve as who you actually build for. And so we're very conscious along the way to choose the right individuals, the right partners that helps shape the product over time. >> And you guys had some some engineering chops and your own Andy Jassy says there's no compression algorithm, the algorithm for experience and then maybe that's an Amazon thing, but I hear him all the time. So you know, they had that to your advantage. And so, okay, so i got your website I see you've got customers so you know, you're well into your journey here. You've got product market fit, I presume you've got you know, your SaaS model your pricing down, but where are you in your sort of journey and you're phasing? >> I mean, geez, those words all change quite a bit these days, I would actually say product market fit is never a binary thing, that the constant journey, right so I would say that we're always working on that because the markets are always moving. And we have a market that is changing month on month and a quarter on quarter, right, so I never want to declare victory on that. Because that's going to get left behind. I think in terms of our journey, like we have on the team right now is 27 people normally based in downtown Boston, We're all working from home at the moment. You know, we have, you know, a sales team in place now of I think six, seven folks now. So we're in market actually pushing this forward. But, you know, I think for us, we're out there really kind of scaling the story right now. I think we've had some tremendous customers we had the chance to work with, we have a product that we're really proud of. I think we just need to put more units out there and more customers to actually make them more successful. So I think anything we're really in the act of repeating every function of the organization right now. It's really kind of build it up. So okay, so I mean, normally when you do a startup, you go to your friends, first the people in your core circles, you get them to that's I'm sure you did something similar. You're obviously beyond that phase of six to seven salespeople, you're starting to scale up, you've probably got a good sense as to that types of salespeople that you're looking for. And then now you're trying to figure out okay, it sounds like how much do I spend on marketing? How does that affect sales productivity? And then how do we scale that whole thing up and then go hyper scale and build a moat and all that other good stuff. >> Yeah, I think you're exactly right, I mean, I think we're at the point now where we can actually start making trade offs, right, like, you know, like, you know, do we actually add a additional salesperson? Do we actually invest in marketing programs? Do we actually build out more strategic product? I think you know, we are still the point we have to make trade offs, right, but the business is mature enough that we can make trade offs right, that makes sense. >> So let's talk about customers, I mean, maybe you could give us some examples, some of your, your favorite examples how you've impacted their business. >> Well, I think if you look at actually our website, I think there's a few case studies up there, I think there's building them up there, there's like salsify books at toast. I think all three of those actually really talk about different kinds of use cases around how we actually affect them. So One of which will we're really helping them actually on alignment, right and making sure that their team is working on the most important things, And, and in those situations, when you're working on the most important thing, you're really kind of essentially getting opportunity cost of engineers and making sure that they're driving towards things that you really will help the business, right so if you're, if you're looking at it that way, you're finding engineers that can help you progress faster, but you're building more product faster, because you can focus the energy where the team is going. And so that's case one, I think another case is really is around, making sure around quantitative management visibility, right, making sure that the team is visible in the metrics and in their output to make sure that they're performing their best, right, and that might mean everything from automated performance management to just making sure that people aren't left behind and making sure that they're the team is actually healthy in their function. And then the last of which is really around capitalization, which is a financial process and really automating that, that's out of the house which is, you know, capitalization requires a traditionally, engineering leaders have to manually fill out spreadsheets for finance, and for the accounting team to make sure that they're actually able to account for where the team effort is going, and then it can actually capitalize it correctly when we treat it from a financial perspective. And so we automate that process that just makes everyone's lives easier. So you're no longer manually data on a week by week basis. >> So I may have obviously seen some of your product and some of the outputs but your your SaaS based model, you know, cloud pricing, all that sort of modern, you know, approaches and business practices. And but what else can you tell us about sort of your, pricing model and how you're going to market? >> Yeah, so I think, you know, we are a SaaS hosted application. We also have, you know, open source agents that have been deployed on premise to actually, you know, whether to work with complex network architectures or deal specific redaction concerns, so we got to operate an on premise environments in that way. You mentioned our pricing is SaaS base we broadly price annually, you know, from broad strokes perspective, it's relative to the the size of the engineering team. Very simply like a, an engineering team of 300 people is a lot more complicated than engineering team of 30 people, right, put it that way. And the pricing reflects that. And then to your question around, like, what else I can talk about? Well, you know, I made the analogy earlier around like they were trying differentiating what Salesforce did for sales. What I mean by that really is providing that executive and leadership visibility to that department, right, if you're looking at the innovation that Salesforce brought in the early aughts, it was really getting stuff out of notebooks into the cloud through manual data entry, and in contemporary sales, I think there's less of that these days, it's all through plugins and voice recognition and stuff. And in the same way, in the engineering side, we're not in the business of actually asking for new data entry. In fact, we connect with systems engineers already using You know, the JIRA is the GitHub to get labs, all they know that their testing tools and their CI tools and then all of those things really we emit what we call engineering signals. So the engineers don't do anything differently. We collect that data, we connect to those systems, we clean that data, normalize and contextualize it with respect to business data. And that's actually where the insight actually comes from. Because if you just look at the raw engineering data by itself, there's not a lot you can do with it, right you know, I joked with you in our kind of earlier conversation, which is, you might look at, you know, your 300 get or request your engineers are produced thing. Like, it doesn't really help you figure out if you're going to do great this quarter, right? And so for us, we really bring that in contextualize it and make sure that you understand it in a business context, to talk about like, hey, is the team accelerating and being successful in the ways that we need the business needs them to do. >> Yeah, you're so right I get a stream of those every day every week and I open them up and I go, okay, I don't know. There's people that work in sort of last sort of topic areas is I want to understand where you want to take this thing. I think I'm writing that you've raised about $12 million, you obviously got a big market seems like you've got a great product. I mean, if I'm you, I'm throwing gasoline on the fire, I want to run the table, you got to create the market . So that's sometimes kind of expensive. Where do you want to take this thing? >> I mean, look, this may sound hubris bowl, but our ambitions are to build a large multi billion dollar standalone software company. And and I think, you know, part of the reason why I say it that way is that I think it's important to have a North star, right. It's important to have a North star to make sure that we're all headed in the right direction. We get the right team members, actually, as we grow the team, and then we actually capitalize it accordingly. I think if you look at the analogy, we started out earlier around sales and marketing. Every time someone's actually cracked that leadership visibility, for each function, there has been a multi billion dollar opportunity there, if not, a multi, you know multi multi billion dollar opportunity out there. So I don't think it's a overly anim facies that where we're going. But I think there's a lot of work to get from here to there. >> Yeah, I mean, I didn't ask you directly about the competition, I did ask you if there's a big whale, is there a big entity, you know, like a database, guys, is they want to target oracle, for example. And I looked around and I, I really didn't see it. It really does look like a Greenfield opportunity, which is absolutely enormous. I mean, I think I'm getting that right. >> Yeah, I think you're right on, and look at I think there are going to be more small players actually entering the market. Like I think whenever we look at new markets, and as they actually kind of build momentum, that always happens. And so of course, I you know, in that sense, I want competition to be here. But right now, I really don't focus on that. I think as for us, It's really about our product in the hands of our customers, how we make them successful. And then let's rinse and rinse and repeat that over and over again to more and more companies. >> Yeah, you don't have to compete you guys have to create. Andrew, great to have you on thanks so much for sharing your insights on your company, good luck with Jellyfish and come back anytime you know, in the future would love to track your progress and see how you're doing. >> Right Dave, thank you so much for having me here and I hope you, your family or team are staying healthy and all this and I look forward to next time. okay, and thank you for watching everybody this is Dave Vellante for theCUBE and startup insights. We'll see you next time. (upbeat music)