Dr. Jeremy Weisz: 07:23
What did you see?
Shriram Sridharan: 07:24
The piece that people are moving data out of these business systems into the warehouse so that they can build a customer 360 on top of it? No longer you just sell a piece of contract and, and off you go and then you come for renewal. People want to be serviced every day. You have to earn the business every hour of every day right? So that’s where the consumption transformation is happening. AWS started it, and all the SaaS companies were following it right along. So which means a contract is a contract, but you get paid on consumption. Like all the account executives started to get paid only on consumption for you to know if the software is.
If your software is getting consumed or not, you need to understand, hey, are there support tickets? What is the product usage? And all the product usage data was in the warehouse. So you just couldn’t tie it to the data in your Salesforce or your data in your NetSuite or in your data in your Zendesk, because they were all not talking to each other at all. So in the companies that we were in all, everybody was moving the data into the warehouse to build customer 360. Right. That was pretty standard.
We thought it was a trend in B2B SaaS. Turns out that’s a trend across all the different verticals we’re selling to paint companies in North Dakota, the, the, if you can take finance like big banks like JP Morgan or whoever it is, industrials, semiconductors, pharma, whoever that is, everybody is doing this. But then the next question is, can you build agents on top to just automate some of the work? Right. So as I said, there are two big transformations happening in the space. One is the data moving out into the. Into the warehouse, and then you have AI agents on top. And every enterprise is now opening the door to AI transform their entire org. It’s either you transform or you die. So that’s the current state.
Dr. Jeremy Weisz: 09:05
I want to talk about a real world example. We’ll talk about maybe MongoDB in a second. But if you’re listening to the audio, we are in the video here. Can you talk about this slider for a second? What we’re looking at, because you can see this has built for account executives. And you can see kind of a daily schedule, email triage, prospect, research, discovery call. And then when I move the slider over, it basically basically goes to discovery calls demo expansion. What am I looking at here?
Shriram Sridharan: 09:33
Yeah. So if you look at, this is great. So if you look at this, this is kind of how a calendar looks like for an account executive or used to look like without Rox, right? So a majority of the time, if you look at it goes in grunt work, which is, hey.
Dr. Jeremy Weisz: 09:48
Email, triage, CRM tab switching, that kind of thing.
Shriram Sridharan: 09:52
Exactly. Research my prospects. Like prepare my QBR slide deck. Like prospect into my customers. And then you have five different tools, point tools that they have, which they have to like continuously switch over to do their work. If they have to do PPG or pipeline generation, that’s like two tools. If they have to do forecasting, that’s another tool. If they have to go and do manual work of entering the opportunity details on what they did, that’s another tab they have to go to Salesforce. So hey, this is pre 2024.
Like with Rox, like most of the grunt work is handled behind it for you. So you have agents that are either foreground or background. Foreground agents are something you come and ask like a chat, and then it generates it for you like a slide deck or, or it could be a meeting preparation or whatever. You could also do it in the background, which is like, hey, Rox looks at your calendar. It knows you have all these meetings today and then sends you all the prep work that you actually should have done. And then you just either listen to it. I no longer even talk and I don’t even type by the way, I just listen or talk to this. And then all the other grunt work of updating your data systems just happens in the background so that you don’t even have to worry about it.
Dr. Jeremy Weisz: 11:08
So this is like before Rox. Yeah. And then this is after Rox. Basically you’re with a customer facing, right?
Shriram Sridharan: 11:17
Yeah. The goal is to get as much time as possible to be customer facing, so that an account executive who was probably doing 100 accounts before could probably do 200 accounts or 300 accounts. So effectively you can help them obviously earn a lot more and help the company earn a lot more. So I would say that this is one of the agents that can actually improve your top line. If you look at coding agents or other agents, they are concentrated on improving your bottom line, which is, hey, can I help with productivity, headcount reduction and stuff like that? Revenue agents can help with the top line. They can actually help you generate more revenue or prevent churn. So if you look at it, we are here to secure and grow the revenue. That’s the mission.
Dr. Jeremy Weisz: 12:01
Well, talk about a real world example in a second, but I do, I’m really curious why you went enterprise because, I mean, obviously there’s a big need for any company. Any company is like, yeah, I want to spend more time on calls and not all the other stuff. But I also see the enterprise probably have longer sales cycles to like to get into these companies. And there’s probably a lot of onboarding stuff and layers that you need to get through on that side. So I’m curious why enterprise?
Shriram Sridharan: 12:34
Yeah, it’s a great question. A couple of things I would say. One is the noise level is very low, right? The lower and lower the stack, you go, there’s going to be hundreds of tools, and with AI you can just getting wipe coding something on a weekend. It’s like very, very fast. And so there’s like so many tools in the SMB and mid market, right? If you go to the enterprise, this noise level is extremely just low, very low, by the way, right? There’s like five tools and we know them and then we can, we can go after them. One. Right.
The second piece is enterprise is durable revenue, right. So you can actually go into the enterprise. You. Yes. The sales cycles are long, but it’s very durable. It’s not your $20 SMB and mid-market ones which keep churning and, and there is no stickiness. The third piece is we. When I started the company, I think we chatted before the recording as well is, hey, our goal was to not sell usage or consumption or seats. We wanted to give you an ROI. We want to partner with you to AI, transform your org as a whole and then provide ROI to the buyer on the other side. Right. So we are invested in either meetings, booked pipeline generated opportunities closed, which is what we’re interested in. And that’s kind of why we went with enterprise. That’s the three higher order bits.
The lower orders as I said, the hypothesis was all the data has moved away from these business systems into the warehouse. That’s mostly happening on businesses that want to report to Wall Street because they kind of have to have the understanding, right. The lower and lower you go. That’s not the bigger pain point we want to be. Initially Rox was Rox Data Corp. We started as a data company, by the way. So we were aggregating all this data from multiple different systems, selling a knowledge graph on top and governance and stuff like that. We then, when we started, all the AI was happening and we decided to actually have agents on top, which could do work. Right? So, that was the second order, if you ask me, the reason for the enterprise and all the founders.
Dr. Jeremy Weisz: 14:41
So like the first one, Ram, was like organizing all the data. And then once you did that, you’re like, well, now we could actually have it do work.
Shriram Sridharan: 14:51
Exactly. So but that actually helped us, helped it be the moat for us, right? Otherwise, we are one of those startups that got killed by Claude Code, right? Or Claude. So if you didn’t like Claude, this is all compute in Claude. The data system is where or the data or context. This was, people call it these days. That’s where the moat is in any of these companies. So we are one of them.
Dr. Jeremy Weisz: 15:13
You know what is onboarding look like? I know we are chatting a little bit about large enterprises. There’s a process and they have to probably connect a bunch of things there. And even when I look at, you know, I’ll pull this up, you know, when we think enterprise long sales cycles, but you it seems like a very almost like frictionless, frictionless. Again, we’re looking at this now this may change. So don’t hold Ram to this. Now we’re looking at the pricing page, but it seems like really a frictionless process because like, hey, we have a free, I remember when I talked to the founder of Jotform and they grew to like 25 million users and a back of a freemium model of people, hey, try it out. That costs real money for a company, right? Obviously, but it got people trying it and then moving to the next level. And you have a free, as of right now, a freemium version. How do you decide on this approach?
Shriram Sridharan: 16:14
Yeah. Great question. So for me, one of the favorite software is Datadog. Datadog is a SaaS company now pivoting to AI. So when you look at Datadog as a model, they do have a free version and then they can also, you can also do enterprise, right? So a product led sales becomes a product like growth becomes like a sales lead at some point when they grow. There are two reasons to do so. One is, since you’re building for the enterprise, it is very much possible that enterprise demands are bespoke, right? So you could build specific things for specific enterprise customers.
Dr. Jeremy Weisz: 16:49
Is this Datadog right here?
Shriram Sridharan: 16:50
Yeah. This is Datadog.
Dr. Jeremy Weisz: 16:51
Yeah.
Shriram Sridharan: 16:51
Okay. One of my favorite companies. So if you look at if you build for the enterprise, you could build bespoke integrations and bespoke stuff for the enterprise and then your product becomes Frankenstein, right? Like nobody understands it. You have to have really a solution architect and all those people sit and help you build the product. But once you start on the enterprise, it’s very hard for you to go downstream because of that where your product becomes Frankenstein.
So we intentionally made sure that, hey, the product has to remain open so that we get feedback from people who just want to try out the product to see what it gives, right? So it forces us to think of the self-serve people who want to try out the product and not just focus on the enterprise, right? Because at some point we want to do it all. So which means you have to keep the product open.
The second piece is yeah, I would probably say we are the only product in this category, in the AI native category which is open where you can come try use it, the entire revenue lifecycle, go through it. You get a lot of feedback from customers, people who are using it, just self-serve. It’s not for the dollars, it’s for the feedback on how people are using the product and you can actually go and improve it. And you can, that becomes a virtuous cycle, right? The third piece of the product is open. Competitors can copy because they can come and look at the product, oh, I’m going to build it in my own product myself. Because these days, once you have an idea and you implement it, people are going to copy it immediately.
You know, Dr. Jeremy, if somebody copies us and out-ships us in terms of both product and revenue, then we are at fault. We didn’t move fast enough. Right. So I think we have a stellar rock star engineering team, I would say. So we rely on the fact that hey, we can outinnovate anybody in this field.
Dr. Jeremy Weisz: 18:38
Yeah. I mean, I watched a talk that you gave, and it was just afterwards you just said, if there’s any other good engineers in the crowd, come see me. Right. I mean, it was a you just want to snatch up as many good engineers as possible. Which was great.
Shriram Sridharan: 18:56
It’s a talent game.
Dr. Jeremy Weisz: 18:57
Yeah, totally. I mean, I could see it’s like, who is an ideal company right now to use Rox?
Shriram Sridharan: 19:05
Yeah. So the ICP is still Fortune 2000, right? So that is the company that we’re going after in any vertical. Like it could be like we already are in hardware, software, B2B, SaaS, semiconductors, industrials, finance, life sciences. So anybody in that vertical, which is in the Fortune 2000 is fair game.
Dr. Jeremy Weisz: 19:26
Got it. Let’s talk through anyways, thanks for sharing that. And anyone it looks like can try it out. But let’s talk about MongoDB, for example. How did they use it?
Shriram Sridharan: 19:39
Yeah. Great question. So Mongo, I think like every other B2B SaaS companies, I think they are in the forefront of technology transformation, a transformation of their org. Right. So, I think when they came to us, I think the idea was top of funnel automation, right? Hey, we have a bunch of BDRs, business development representatives who actually are outbounding to these companies and the way they outbound is they have signals that live in their warehouse internally. And then they, and then there’s public data that we can go and get from the public internet. Can you help automate this process where you can do personalization at scale, right? For them. So that’s their inbound.
And then the metric is not just, hey, we are a platform of its usage. We have to hit numbers for them, which is what an actual human is comped on. Either you have to hit, we have to hit like a reply rate, a bounce rate, and an open rate. And we will. The next piece is push it through to see can you get meetings on the calendar for them? And the next piece would be, is this a qualified opportunity at all in the first place? Right. So as I said, we are here to sell work. So we just not build a platform and actually give it to them. We have a full forward deployed engineering that actually sits with the customer, understands their process, and then either use Rox headless, or you can use Rox as the product that everybody logs in to actually do work. Right? So that’s the, that’s the higher order value prop.
So you looked at the image above. So if you go about. So this is pretty standard now, right? So there’s horizontal agents that’s everywhere, which is Claude and other companies. And then there are vertical agents for R&D support and sales. So this is what I talked about. So R&D is coding agents. And then there’s support agents. And then we want to be the vertical that we want to be the company that dominates the sales agent space or the revenue agent space.
Dr. Jeremy Weisz: 21:47
Is it replacing software, like what software is replacing from companies? Or is it just laying on top of some of their software to help?
Shriram Sridharan: 21:55
Oh wow. Great question. So yes. So at the end of the day, if the agent is doing end to end work, you won’t need the SaaS, right? So you can consolidate a bunch of software. So if you look at this space, of course, there’s.
Dr. Jeremy Weisz: 22:06
Like, let’s say they use a platform now, Ram, to send out emails, right? Is Rox actually setting out the emails, then through their through system.
Shriram Sridharan: 22:15
Yeah, yeah. So I’ll talk about in general what the vision is and I’ll talk about MongoDB next and what they do, right. So the general vision is in this space in the enterprise, you have the CRM by by far in default, it’s like Salesforce or Dynamics, right? So those are the enterprise terms. HubSpot is mostly SMB and mid-market. And then you have the tools which are doing different kinds of point tools, which are different things. One is you have enrichment and you have a bunch of companies which do enrichment, and then you have enablement, sorry, you have engagement, which is sales engagement, and then you have conversation intelligence, you have revenue intelligence, and then you have some automation right now, right? So that’s kind of the different verticals on top with the CRM in the back end, right? Our vision is to do it all like you have agents, which just does it all for you.
Dr. Jeremy Weisz: 23:05
So for instance, you know, from like, let’s say someone’s using Salesforce and they use something like Clay, like Salesforce, and they use like Clay, like enrich it. And then they use something else to send it. You know, they send it out through Salesforce. Like that’s basically Rox can do these various steps, right? Is that accurate?
Shriram Sridharan: 23:22
That’s correct. So right now we are in the agent orchestration space and we’ve consolidated all the data that is across their warehouse, their internal Salesforce, public signals. So that’s, we kind of build a knowledge graph on top of their data. And then we have the governance layer that sits on top. And then we have the agent orchestration, which helps to generate the personalized emails, but they still send through their sales engagement platform, right? Because that’s where you have to transform the org to be like, hey, come and use the sequencing in Rox to start doing that. But that’s where the forward deployed enablement and training and all those things happen for people to do that over a course of time.
That’s the copilot way of doing it, right. The autopilot way of doing it is just Rox sends the emails. If the reply comes in, we will actually the, the agent will just send a response back automatically and then book a meeting on your calendar. So you only, as you said, when we started off, you saw the slider. You only have meetings on your calendar. Everything is just abstracted out in the background. That’s the vision where we want to go to Dr. Jeremy in MongoDB. Right? So, so but if you imagine this, this is not happening on day one. It’s a you have to do it over a course of time because there is trust and verify. The AI can do a lot of things, but people have to trust that it is doing the right thing because their brand is on the line. And all that stuff. So yeah, I think that’s the journey that we are on. And we will help transform organizations in terms of their AI journey and we are in AI partner.
Dr. Jeremy Weisz: 24:51
So you mentioned, you know, trust and verify. I’m wondering how do you train it then over time, because maybe there’s different steps like, okay, now I’m, I see the email spitting out. I’m not automatically having them send something. Yeah. You know, does it get trained? Or I’m maybe it’s connecting to their different systems, I don’t know.
Shriram Sridharan: 25:11
Yeah. It’s a great question. So a couple of things. One is you could tune it in the product, but then you could also provide samples in terms of how you have done this before. And then, the third piece is the agent actually learns based on what is getting opens and replies so that it can be a feedback loop into how do I optimize this further? Right. That’s kind of the holy grail because there is a self-optimizing loop in terms of what is actually helping you get replies and opens. So that is a function of the context of the data layer that I talked about, right? Hey, you have a lot of data in your warehouse. It contains content that comes from people visiting the website. It could be somebody using MongoDB in a GitHub repo somewhere.
And then so all of these data that is either public or private, you have to understand, you have to filter out the signal from the noise, right? Hey, do you have all this data? What is the signal that’s actually helping you drive your outbound reply rates and meetings and optimizes completely. So you need the entire stack for you to do so. And you need from the data layer all the way to the agent orchestration to the SaaS, which actually does this. And then you can, the agent can close the loop. That’s the business that we’re in.
Dr. Jeremy Weisz: 26:19
What, I’m curious, you know, Ram, what objections did you get from some of these companies? I can see, I mean, maybe they just don’t want to change. Obviously you with all these companies that serve you, you overcame a bunch of objections because they, they probably have stuff they’re used to using. And it’s hard to get people to change. I think what were some of the objections that you were getting that you had to overcome in the process?
Shriram Sridharan: 26:49
Yeah, yeah. So I mean, first of all, like connecting data, there is a huge security legal.
Dr. Jeremy Weisz: 26:55
Like we want it to be private. What are you doing with this?
Shriram Sridharan: 26:59
Yeah. They won’t connect. They won’t connect the data. Right. So that’s the first piece. So we just have to start off with just public data to prove value. Hey, we can just use public data and we can prove much more value. We can drive revenue to you guys without any connection to the private data, by the way. Right. So that’s kind of the land motion we land with saying, I can help bring ROI with just helping you just with public data, right? This is just from an exec perspective. Then over a course of time we get. They can see the value that is being generated and then they allow connection. Of, let’s say emails or calendars or Salesforce.
From an adoption perspective, from a user perspective, right? It’s a completely different workflow that they’re doing now from what it is before. So for every company, the workflow is very different. Like when you go to a, when you go to an industrial, when you go to MongoDB, when you go to a semiconductor, every workflow is different across these companies. So you have to first learn and understand what this workflow is and how Rox fits into the workflow. You just can’t sell a product one size fits all. And then and then just go from there, right?
So I think the bigger piece is like, you have the two things. One is you have to have an internal champion who is also working with you to ensure that everybody uses the product and is able to drive value from it. Because getting the internal champion is very important because they are the ones who are your partner on the other side, who is helping you drive that change from within. And then from your side as well, the product also has to surface what they want in the workflow that they are. Because nobody wants to log into a new tool, right? So how do you get them to log into a new tool, which actually helps them in a way that they can do what they want to do. So those are the challenges that you have to kind of overcome when you’re selling to the enterprise.
Dr. Jeremy Weisz: 28:46
I’m going to ask a very geeky question in a second, but we will talk about, I want to hear about WSP also because their example is interesting from going from static lists to smart signals. But my geeky question Ram is more of a technical thing because I do kind of geek out on cold email, not just the copy piece, but also the logistics. Because I know like if you’re sending a bunch of cold emails out to people and someone marks this spam, they can put you in a separate, you know, box. So I know a lot of people doing this have a number of domains that they’re deploying. So in case someone marks it as spam.
So in your case, I’m just curious and you don’t have to get into a whole long technical. Are you managing that on the back end through Rox? Because if you’re sending it to people they don’t know and someone marked it as spam, obviously, you know, there’s multiple domains that people usually rotate between.
Shriram Sridharan: 29:40
Yeah, yeah, yeah.
Dr. Jeremy Weisz: 29:41
And you’re the CTO, so I’m sure like you don’t have to give me like the super technical, but I’m just curious, is Rox managing that on the back end if they’re just using that?
Shriram Sridharan: 29:50
Yeah, yeah. So Rox does manage it. The deliverability is a problem.
Dr. Jeremy Weisz: 29:54
It’s hard. I mean, you’re handling a lot of difficult problems here with your system.
Shriram Sridharan: 30:00
Yeah. Yeah. Yeah. So I mean the piece is I think it’s not the volume. It’s the timing and the content, right? So like, I think, I mean, you’ve probably heard of signal based prospecting. You have to have the right signals and sent to the right people. If you’re just cold emailing a bunch of people, I mean, it’s the, if you get three replies for ten people and then 30 replies for 1000 people, like it’s probably the rate becomes the same at the end of the day. Right?
Dr. Jeremy Weisz: 30:29
That makes sense. If like they’re signaling like, I want this or I like this, then they’re more likely to click on it because it’s of interest to them. Right. I’m with you.
Shriram Sridharan: 30:38
Yeah. So that’s kind of how we get over the deliverability problem. But we also have like multiple domains. We handle all of that internally.
Dr. Jeremy Weisz: 30:45
That’s tough. My God, you’re handling a lot. If anyone’s done it before, it’s like it’s super challenging. But that’s what the moat. That’s what you’ve built. So that gets me to WSP. How do they use it? What’s the use case there?
Shriram Sridharan: 31:00
Yeah, yeah. So yeah, WSP is very interesting company. So WSP is one of those companies which came into Rox because the product was open, right? We have no prior relationship. They tried the product. They were one of the earliest to try it. And then they reached out to us.
Dr. Jeremy Weisz: 31:17
They have over 50,000 employees.
Shriram Sridharan: 31:19
Yeah, they’re a customer, by the way. Right. So they’re also very, very good in terms of what they’re looking for. So I think in WSP, the thing they want to do is RFP automation, right? So WSP cells, they kind of help, help build or construct bridges and other things in Canada, right? So they have to know if there is a request for proposal in a Canadian website in any of the, from the government. They need to know what the proposal is. Is this proposal something that we can handle and then submit the proposal? More often than not, the first one to submit the proposal wins, right?
So what Rox was able to do just this is one of the examples of just public data, right? There is no private data in here with just public data.. We are able to, once we have the domain, we’re able to detect the RFP. And then we were able to send them insights on, hey, this is something that you have to submit. Now we have gone on to actually do and go and filter out the RFPs. There’s some business rules in there to filter it out and then fill the RFP and then send it across to them.
But this was being done manually by them, by a huge team sitting and researching Canadian websites and understanding and doing it every day. One of the examples where AI just clearly drives top line value, right? So we were able to get them opportunities in terms of multi multi-millions, which they manually, even when manually doing could not have got into it in terms of the breadth of what Rox was able to do.
Dr. Jeremy Weisz: 32:55
When I hear that term RFP, I want to just, I’m like, forget it. It’s too, too much work. It’s too stressful. Right. So it’s a good problem to have if someone out there does submit a lot of RFPs. This is great. That’s great. And on a different front, You know, there’s different companies here. Maybe talk about large industrial company and how they use it.
Shriram Sridharan: 33:23
Yeah.
Dr. Jeremy Weisz: 33:23
So and by the way, this is instructive, I think, for anyone from, you know, for let’s say, I mean, you could go and Rox has like a free version, you could actually check it out. But you know, I just think of how do people use, how do they think through AI and use your system? And that’s just a way of thinking. So even if I’m like, I’m not going to use AI or whatever, but it’s for me, it’s instructive regardless of how you can think through some of these processes. So yeah, I’d love to hear that end from a large industrial.
Shriram Sridharan: 33:57
Yeah, yeah. So WSP is one of those large industrials.
Dr. Jeremy Weisz: 34:01
Oh it’s one? Okay.
Shriram Sridharan: 34:02
It is, it is one of those. So we did hear that. But I mean I can give you another example which is we can take let’s say Bynder that was on the top. So if you go up. Yeah. If you take that example, I guess. Yeah. So it’s also sort of account research where people were doing right for them, they were trying to understand their competitor on, hey, what are the places the competitor is selling? Right? So for that, we had to go and our research agents, which is one of, was part of the account research that we do, they’re able to go and find kind of domains that the competitor has set up somewhere else. Right. And then from the domains, the agent infers that, hey, this is the competitor who is actually selling into this company. And then Bynder can run a stakeout campaign on that. Right?
So if you see that’s a signal to understand, hey, what do I go after? And then once you have the signal and then plugging in your value into those companies to say how you can do faster, better, cheaper and reach out to the right person is something you can completely automate out. But the point is, the research is the bedrock for all of that, right? Otherwise, you’re just cold emailing like 100 people and you don’t know why. There are no responses. So you do your research first and the agents kind of do the research and the agents kind of outbound end to end, which kind of drives ROI.
Dr. Jeremy Weisz: 35:34
Yeah, I think the signal is really key. And sometimes finding the signals is really hard and it’s very fragmented to get that. So.
Shriram Sridharan: 35:48
That’s the whole point of us consolidating all the data in a warehouse. So if you have all the signals, which is private, unstructured, which comes from private structure, which comes from your Salesforce and other business systems, private unstructured, which comes from your like, let’s say this call is recorded, the transcripts, emails, all the sales enabled materials and public unstructured, which contains this company raised funding. Was there an RFP that was outside that was proposed? Right.
So once you are able to stitch together all this information, Dr. Jeremy, then you can run agents on top, which can do the entire revenue lifecycle. You can prevent churn because you’re looking at product usage to understand if the customer is using the data or not. You can also generate a slide deck to go and run your deals. And then you can meeting prep, you can do inbound, outbound, and so on and so forth.
Dr. Jeremy Weisz: 36:40
Yeah. The question that pops out for me on this is like, what are the signals, and this is for any company really, what are the signals right before someone makes a decision or to use a solution like yours? Because if someone could figure that out and maybe some people haven’t thought that through, but obviously your solution kind of helps with that piece, I imagine.
Shriram Sridharan: 37:05
Yeah. I think that’s the piece that we also help figure out, right? Because it’s like there’s no silver bullet here where you can say, hey, this is a signal. That’s it. Let’s go get some money. Right? That’s not how it works. You have to.
Dr. Jeremy Weisz: 37:17
I mean, there’s some obvious ones depending on what industry someone’s in, right? Like if it’s like a IT solution and someone’s been hacked. Right. That’s a pretty strong signal that someone’s going to search for IT. But a lot of them are way more subtle than that type of.
Shriram Sridharan: 37:33
Yeah. Yeah, absolutely.
Dr. Jeremy Weisz: 37:34
Yeah. I’m curious about your team a little bit and how you met your co-founders, because there’s several co-founders here. How did that come together?
Shriram Sridharan: 37:47
Yeah. So this is where serendipity kicks in. So I was in AWS for around eight years. As you, as you introduced, I built Aurora. And then I was at Confluent building Kafka. Right? I did not have my immigration sorted out. So I could not go and start something of my own. Right. So I had to leave the country, come out. I didn’t get my H1 one for like eight years in a row. So and then so all of that was happening in the background. So I’ve always wanted to start something of my own but just couldn’t.
Dr. Jeremy Weisz: 38:16
You needed to be employed to stay in the States essentially.
Shriram Sridharan: 38:20
That’s pretty much it. Yeah. So I came to the States. So that, I mean, this is the land of dreams. So I wanted to start something of my own, but I was stuck on the immigration queue forever. Right. So and then it took me ten years to get out of it. But now that I was out, I was going to start something of my own. So Chris Ré, who is who you see on the screen, he was my professor in Wisconsin. He’s from Wisconsin. He moved to Stanford. So he and I, we kept in touch in terms of what I wanted to do when I was ready to start something of my own. At that time, I mean, it was just serendipity that he reached out, the professors reached out to say, hey, Ishan, Ishan is a serial co-founder, serial founder. He’s done two companies before. He understands the game.
They reached out to say, hey, Ishan is looking for a technical counterpart. Do you want to go talk to him? Right. I was thinking of starting something on the infrastructure space, and then Chris and other other professors rightly advised, hey, this is the age of AI. Like, do not do anything on infrastructure. Just go do something on AI. And that’s kind of how I ended up meeting Ishan. Ishan and Diogo kind of knew each other from before. But both of them were looking for somebody who can be the technical counterpart. So that’s how I met him. I was building large scale distributed systems and platform. Right. AI was new for everybody, but I didn’t know anything squat about the sales vertical because, hey, I’m building the database that powers Amazon.
Dr. Jeremy Weisz: 39:48
If you could do that, you could do anything, right?
Shriram Sridharan: 39:50
Yeah, yeah. So I mean, that was a confidence, but also the piece that, hey, I came to this country to start a company because that is my desire to, or I mean, in Amazon, in Jeff Bezos, I highly respect him. He is a framework which is called the Regret Minimization framework. Hey, you should, don’t regret when you’re 60 that you didn’t do something right. So if I had not started a company of my own, I would regret it. I knew it for a fact. Right. And so, that desire was there for a long time. This was serendipity that this happened. The universe kind of conspired with me to kind of get in touch with Ishan and Diogo. They are just stellar, stellar people. And then me and Ishan talked for a month before I decided that, hey, yeah, this is a problem because I mean, you are every day building systems. You’re thinking about that problem and I have not thought about this problem where, hey, is this a problem in this vertical?
So I had to go do my own research, understand is this really a problem? Talk to a bunch of account executives and BDRs who I’ve never talked to before. I’m like, hey, these guys sell, I built that was my split. Right? And so I was like, building something for them. So I took take a month to figure out if this is really a problem. And at the end of the day, Chris and Ishan, they have done, they’ve monitored for a while. So yeah, I mean, I trust them, I trust their gut and instinct, but that’s kind of how I took the leap. But over the course of time in the last two years, there is yeah, there’s absolutely this is a place to be.
Dr. Jeremy Weisz: 41:30
It’s pretty wild. So this is not only a SaaS AI series, but I do a Wisconsin Entrepreneur series. And so this is now part of that too, because I obviously had a bunch of Wisconsin entrepreneurs. You know, Ram, my last question, first of all, thank you. Thanks for sharing the journey. Thanks for sharing your expertise and Rox. People can check out our Rox.com.
Just the last question is about resources that could be mentors, people have helped you. Obviously, you mentioned some of your co-founders there. It could be just books or podcasts that you like as well. In this space, you know, people you learn from distant or people who have mentored you in business as well through the journey.
Shriram Sridharan: 42:14
Yeah. I mean, books, you said, I think one book I do really love is Extreme Ownership. I don’t know if you’ve.
Dr. Jeremy Weisz: 42:21
Jocko Willink yeah.
Shriram Sridharan: 42:22
Jocko is an amazing book. I mean, I think, yeah, some of this in that book is, hey, it’s a leadership problem. It’s not a team problem. Right? It is a leadership problem. So I think that book is phenomenal. It’s helped me a lot to start, because I’m a first time founder to start thinking as a founder. I think that book is pretty good. From a people perspective, I think, I mean, there are so many people who have helped me, but I would I mean, it would be injustice if I don’t mention my dad for sure. I think he is an inspiration. He gave up his career so that I can come up in my career. So I kind of stand on the shoulders of the.
Dr. Jeremy Weisz: 43:02
What was his, what did he do for a living?
Shriram Sridharan: 43:04
He’s been a bank accountant for 40 years in India, in India somewhere.
Dr. Jeremy Weisz: 43:08
Okay. Is he still there?
Shriram Sridharan: 43:10
Yeah, he’s still there. He retired. So he’s now I get retired having fun. But he did not move. He had a lot of opportunities to actually grow in his career. So. But he did not take any of them so that I can study and then like come up in my career. So he’s an inspiration. So he kind of sacrificed a lot so that I can be where I am. So definitely him. The second piece is my wife. Like, I just, I, I think I told you this, we just recently had a kid. He’s one month old now. I just cannot do this. This is high stress, high stress, high, high.
Dr. Jeremy Weisz: 43:48
You look well rested. That means your wife is not.
Shriram Sridharan: 43:50
So my wife is taking care of. She’s doing a lot of heavy lifting. So, I mean, there are other people outside who actually like, inspire and motivate for sure. But these two people in my life. They are the biggest source of support and inspiration for sure. Right? So I would actually dedicate everything to them.
I think you said podcasts, there’s a lot right now. 20VC is something that I watch all the time. And then there are others where I guess Satya and Sundar Pichai and all those people, they come and do podcasts on that shows up on my YouTube feed when I’m driving back from home. Those are things I listen to. So I think, yeah, those keep me going.
Dr. Jeremy Weisz: 44:31
I love it, Ram. I’ll be the first one to thank you. Everyone check out Rox.com. More episodes of the podcast. We’ll see everyone next time. And Ram, thanks so much.
Shriram Sridharan: 44:40
Thank you so much for having me.
