Reinventing Billing & Quote-to-cash with Sequence Cofounder & CEO, Riya Grover

Hey everyone, welcome to the "Water & Wind Tech" podcast. Today, we are joined by Rhea Grover, co-founder and CEO of Sequence, an AI native revenue platform that unifies coating, billing automation and receivables operations. So companies can run finance at the speed of sales. Rhea talks about her journey in building and growing sequence, insights from her recent fundraising journey, and she has a special announcement to make, so stay tuned to the end of the podcast. Glad to have you on and very good to finally meet you. Yeah, sure, and thank you for sleep by the way for having me on. Great to be here. Very excited to dive deep and learn about sequence, see her for tech stack and especially your journey. Let's start with you. Talk to herself about your journey from the early days of investment banking and Harvard Business School to being a second-time founder and CEO now. What led you to those places and what led to you moving on to your next chapters? So yeah, I graduated from university, did economics and started my career in banking and it felt like, you know, we had a fairly sort of defined path, like you go to banking or you go to consulting and that's a strong and sensible, sensible default when you graduate. And I've got to say, like, I really enjoyed my two or three years in banking. It was fun, fast paced. I learnt a lot in terms of how to operate, how to be heard, how to make decisions quickly, how to navigate people in these kind of very large bureaucratic contexts. But the truth is, finance didn't excite me at a fundamental level, personally. Couldn't see myself building a career in that domain. And I think when you're in a bank, like, it's very easy to convince yourself to stay. Pretty kind of rapid progression and it's an exciting place to be. But I made the decision to go to Business School, you know, after I became an associate. And really with a view to transition to an entrepreneurial path, I knew I always wanted to be a founder, thought, you know, Business School would be a nice leader, reflect online, get the confidence to then actually go and do it. And as a result, went to HBS and immersed myself very deeply in all of the venture and entrepreneurial related things that were happening on campus and started my first business right out of HBS, was building a food tech marketplace. So connecting independent restaurants to corporate buyers and with this sort of two-sided platform, we scaled that, it raised a little bit of capital, but not much. So pretty lean and scrappy team and we scaled that pretty quickly over three or four years. And over time also developed a software component to the business where we had this two-sided marketplace, but we'd also developed a set of software that facilitated orders and payments and in the middle and actually started then also selling that software as a kind of white-labelled offering to other restaurants and groups. And actually, so while I was doing that, the software business that had spun out obviously had far more attractive dynamics in terms of the margin profile of the business, but also we were seeing really strong adoption there. And then in 2020, we got a pretty compelling acquisition offer from a public company called Compass Group to buy us because I think they saw an opportunity to embed that software across their 10,000-plus outlets across the world and also to leverage some of the elements of the marketplace platform that we built. Given we had not raised much capital and sort of owned a large part of the business of that point, the offer was really compelling, we decided to sell the business. I think that was a great first run and got to experience being a founder and loved building a business, loved building a team, but I decided I wanted to build something orders of magnitude bigger and really build the software company that went to being a unicorn and beyond and decided to go really properly down the venture route to do that, raising off capital to really build a big business, hire the best team that I could and take some of the lessons I had from the first time and channel that into the sort of next milestone or next level of success. So Fida was my first business and sequence was really born out of a pain point I experienced whilst building the first one. We were a B2B software business that had custom pricing, custom contracts, pricing evolved significantly over the journey of building the business and when I looked at the revenue platforms out there with the revenue infrastructure, Stripe is really good for e-commerce, self-serve, very simple, vanilla subscription businesses, isn't really designed for the B2B economy. Then on the other hand, you've got a bunch of legacy incumbent players who frankly don't move at the speed that you need to as a next generation fast scaling B2B software company and saw a really interesting opportunity to build a really AI first workflow automation first platform that takes the B2B company to automate kind of pricing, billing, invoicing, essentially collect revenue really seamlessly against all of these custom contracts that it's signing in the business. And for me, it's a really powerful mission because ultimately you're really like fueling the growth of these companies or this underlying backbone infrastructure. And if you think about it signing contracts and collecting revenue are the most important things that a business has to do and you're really acting as that foundational infrastructure to be able to do it and enabling companies to adopt a product very quickly and also very frictiously, frictionlessly change things or really scale with you. That makes a lot of sense and I definitely resonate with a lot of your motivations early on. When I went to the background, I didn't invest in banking for six years. Do you feel like there's an edge that I want to build something when that edge is there? I think it's it's really hard to shake it off. My parents were both entrepreneurs as well and went through a lot of highs and lows while we were young. But I think like dinner table conversation was pretty much always that like the company that they were building together. You know, if they were talking about something, it was that if they were fighting about something was that. I feel like there's some deep intrinsic motivation there to do the same thing that embed from a very early age. I can imagine those would have made for very interesting dinner time conversations. Thanks for giving us a peek into sequence. Historically, accounts receivables and go to cash process seems to have been the unloved area of finance. Would you agree with that and what makes it hard to solve? Yeah, it's a great question. Actually, I do agree with that, which is really why we're we see a big opportunities to tackle the category and build a category leading business here. I think if you look at something like AP accounts payable and spend lots of large, very successful players have come up in that market, you know, businesses like RAMP and Brax and zip and others. And you almost take it for granted today that your workflows on the spend side, you know, should be seamless and automated. So if you submit and receipt to kind of for an expense reimbursement, you know, that receipt is automatically the data is automatically extracted, it's one click to review. Now you have AI agents that might pre-review it and only pass it on to a human if there's something that seems out of policy, for example, or you forward an invoice and to be paid. And like, it's pretty much a one click workflow if that to go and pay those invoices. So definitely you have seen a ton of love and a ton of workflow automation on the spend side and also a number of other verticals within the CFO stack domain. You're right quote to cash revenue has not seen that happening yet. And I think there's a few reasons for that. One is revenue is harder and so far as it's not one size fits all. Everybody might process invoices and pay them in the same way. Every company has their own pricing structure, go to market motions, flow needs when it comes to revenue and revenue collection. And so the challenge there is can you build something so flexible out of the box that actually allows for a company to configure, you know, quoting, laying in, voicing to meet their actual business model, the actual pricing model out of the box, which I think a lot of legacy incumbent players have not done because they were built around this notion of like, well, every B2B business charge is based on simple fix recurring subscriptions or built for a subscription economy, not the way contracts and pricing structures where they look today, then inevitably in order to go and actually implement one of these legacy tools like a maxil or charge be something. If you're doing anything outside of that vanilla subscription model, it's a pretty painful to go and configure it to fit your pricing model or your contract structures. So that's one revenue is not one size fits all. I think the second piece also is that AR revenue has typically seen lots of different point solutions pop up across the workflow. So you've got CBQ tools that manage pricing configuration of contracts. You've got billing tools that do the billing and voicing. You've got different revenue recognition products that will, you know, tell you how revenue should be recognized against those contracts. You've got done in cash collection tools that will be point solutions to chase your invoices. And so it's not a typical to see a CFO with like four or five different tools in this stack to just manage this workflow. Our point of view is actually most of the problems of inconsistencies and data errors like the pain of actually working and transferring information between these systems come from this fragmentation problem where everything is happening in these different systems, where's your source of truth for something as there's a discrepancy, where do you attribute that to? I also have this traditional problem where people are trying to build an integrator between what's in Salesforce and what's in NetSuite, for example, and actually you're missing some critical tooling in the middle to be able to really have that that bridge be very seamless. I guess all to say our point of view is that all of these workflows across that cycle or really stem off that upstream contract data record. You can capture the terms of those contracts upstream really seamlessly. You can power all of these downstream workflows and you can do so in a way that is like far more efficient than having these disparate point solutions across the stack. Even AI is like a big catalyst for that. The reason being that you can embed some agentic automations into this workflow to make things like data capture or some of these repetitive tasks easier. We now are able to capture sales contracts upstream using AI and map whatever is in those contracts against a company's product catalog. We're able to use agents to automate cash collection and send follow-up emails and ultimately manage unpaid invoices, great kind of LLM use case. I do think that consolidation is something that hasn't really been done effectively before and provides a massive benefit to really achieving the kind of work for automation that you're looking for. It seems that the key punchline here is being able to manage very bespoke and customized contracts all in a seamless and integrated manner, so that's single touchpoint for Salesforce and revenue teams. Just mention AI and if you do not speak about AI, this would not be a podcast. We have to get into it. In my observation over the last couple of months, I think, as far as adopting AI is concerned. I've seen a slight shift in the conversation from what's the next cool capability we can bring using AI to how can we improve our existing workloads, how can we crystallize some of the efficiencies that we can see immediately. In your experience, has that been in the trend, would I also like you to touch a little bit about what are the areas where you're seeing AI and agentic tools actually moving the needle in finance workflows? Yeah. A ton to unpack there. On the point of kind of tools, there are obviously a ton of new tools on the market. Some of them sort of wrappers around GPT and other LLMs, but with meaningful additive value beyond just what you can do with those underlying models, let's take something like a cursor in theory, I think, open AI could build a cursor, but there is something about focus on the UX and the experience that the cursor team can bring when delivering that, that ultimately means that it's a really purpose-built product with a single focus on that job to be done, which ultimately means it will deliver value beyond just doing this within open AI's platform directly. I think there's a really interesting debate about some of these tools which are just wrappers around these core models, so do they have longevity in them? I do think there are some who will be able to create those modes and the rate at which their scaling is pretty unprecedented as well. There is clearly demand for these kinds of automations and some of these things that shipping marketing posts or writing copy or writing code, and there's a path to more commoditization or democratization of what otherwise used to be confined to an engineering only skill set or someone who actually studied computer science, so I am really excited about some of those tools and an evolution, but what I'm personally more excited about is how enterprise software applications will embed each and take capabilities in and around the core software offerings, and I think in theory, if incumbents did this well, they are the best place to win from these changes. If Salesforce did this well, they've already got the distribution, they've got the deep-rich data sets, they have really the power to leverage genetic automation in a way that an entrant doesn't, but the truth is, when I look at most incumbents in the market, they will not do so effectively, and I think the reason for that is to really embed egenetic workflows into your core software application. One is you do require, let's say, some architectural changes that are just harder to achieve as an organization. Two, as I think you really require a different product mindset in your team that is, again, harder to embed retrofit when you've built hundreds of thousands of people into your org, who have not necessarily grown to be AI native. Now, I have seen some big organizations change that very quickly, but it's really hard to do. And I think the result ends up being you end up as an incumbent, probably adding relatively superficial AI based automation, but not deeply really changing the workflow, because to change the workflow, you really almost need a new UX pattern altogether, that you're not just talking about human to human handovers of tasks in the product, you're talking about human to agent or agent to agent. And that just requires a different way of thinking about software, using software. You go from doing more in software to actually reviewing more, and again, just those interfaces need to really look and feel fundamentally different. And so when it comes to enterprise software and agentic automation, I actually think the earlier players, you know, sequence included, are the best place to win, because there is a lot of workflows and tasks that happen in these tools that are very ripe for organic automation and can really enhance. And our bet is that it's really, really hard for incumbents to retrofit those. So if you're born with a more AI native mindset, you know, every single piece of software you're thinking about, well, okay, how does an agent interact with this? How much of this is a human doing versus an agent doing like work in an LLM and hunt this workflow? And you embed that into the core application as opposed to not to thought around it. Yeah. I'm personally excited about really what that means in the financial operations AR, revenue automation space. I think it's a very natural domain. In terms of your question of, where else have I seen really smart use of agents across the finance, CFO stack, I think there's some really cool things happening. You know, we use ramp, for example, you know, on the on the spend side, there's a, I know, there's, when I get an expense to review, there's flag to me subtly that, you know, this one seems kind of out of range or this one looks fine. This is consistent with, you know, everything that's been submitted before. So if somebody submits a lunch expense, I don't really need to internalize whether that makes sense or not, whether that's accurate because I have this agent kind of alongside me supporting me with that. And that's a great example of where it's not like you can't do it without, but it definitely speeds up your workflow. Another place I've seen this is with like bank reconciliation, you know, we've got hundreds of transactions you're trying to reconcile an agent recommending what that should be. I think you used to be able to do some of this with machine learning with decent accuracy, but I think LLMs are even better. So now instead of you having to review a percent of transactions, you're able to review five with a much higher degree of confidence, lots of products I'm seeing about querying data and pulling insights. I think there's still an asset, so things that are built more for corporate finance teams. Things still relatively nascent there because obviously there is good as the underlying models, but I think from a user experience perspective, there's something pretty compelling about being able to just, you know, query your net suite data or query your billing data with that natural language based interface. And we're also doing some really cool things on the agent side as well. I just gave you that example of ramps, policy review agent, actually we're doing something similar on the receivable side where when companies issue hundreds of invoices to their customers ready to go out, a finance team typically wants to check those invoices before they go out the door to make sure they're correct, even though they've been automatically issued and created, it's a very natural human thing because it's so important that you want to check those things. And this can, you know, often take hours, it's mundane, it's repetitive. With our invoice review agent, essentially the agent will take a first pass of those invoices and flag notes alongside it if anything looks anomalous, there's a discrepancy, and it just means that that human is going more from doing to reviewing where they are having just really only focus on that 10% of invoices that the agent has said you should really look at these. And so I think that's just a great example of like agent working alongside human as part of a core workflow, but it's not as simple as just putting a chatbot onto your platform. You've got to really embed it in every interaction now changes because there's another player in the mix, which is this agent. I think to your earlier point that incumbents are much better placed in terms of doing so, I would imagine that one of the key advantages that sequence and let's us some of the other incumbents have is not necessarily the tech, but also the deep expertise and understanding of the finance workflows. Also, you know, innovation compounds, so it's not just about who gets an agent in Vasta. It's very soon you're going to have multiple agents in your platform performing work. They're going to be garnering insights. How do you leverage those insights? How do you get agent agent working both within your platform and other platforms? So it's not just about this first cycles of innovation, but the fact that they will compound and then the gap between incumbent and entrant in terms of really how powerful that their software or their platforms are, that I think the wedge becomes really significant. I'd love to take you back once again to some earlier days. Sequence has grown quite quickly over the last three years. What signals told you that you had hit the product market fit? What really gave you that confidence? It's funny. When you look back on anything, you can go off and you're like, oh, it's sort of straight into the right. It all seems like it falls into place, but I didn't find any product market fit for any software companies is really one of the hardest things to do. There's no industry by default that is not somewhat saturated. The market is definitely not competitive if there's an obvious problem waiting to be solved. When we said about to do this, we saw that there was a big opportunity. There was no category leader in the space. There's a clear pain point. We talked to hundreds of CEOs and finance teams who would say, yeah, like it's a mess. My contract data is scattered across Salesforce fields, email threads, spreadsheets, just figuring out what to build with the sales team is taking me days, invoices are out the door eight days after the month finishes. Clearly, there's a problem here. It's a data problem more than anything else. When it's a data problem, that's where technology is great to come in and solve it because if you can streamline that data and then have the right rules and push it to the right places, there's a problem there to be solved. The reality is, when you start working with organizations, you're trying to solve this multi-step problem. It takes time to figure out where you can wedge in. Second is that billing, pricing, CPQ is a huge product surface area and every company has their own edge case. You start working very early with some design partners. One has seat-based billing with milestone-based terms. One has usage-based billing with multi-year pricing step-ups. In the early days, you're trying to de-scope as much. How much you build in the first month or two is really hard to figure out where you draw the line. With the theory, you've read the books, try and find as much overlapping demand. Make sure you stay true to who your ICP or ideal customer is as opposed to selling out to service like the wrong type of customer early. You know of this stuff theoretically. When it actually comes into practice, you're pulled in so many different directions and actually sometimes in those early days, it's pretty hard to abstract the patterns because you don't yet really know what the patterns are. When I look back, some of the things that cut the cycle down to be as short as it could be. One is choosing high-quality design partners where there was really an acute need and they look like the type of customer we wanted to have in the business. It takes a bit of while to get there, but once you can get enough of those, that's very powerful. Really trying not to be distracted by ad hoc requests that are pretty niche to that customer to really think about what building for broad looks like, again, a lot easier said than done. But when I started to feel we really had product market fit, is when our product was in the hands of enough users, probably 10 or 20 users at least. Those users are talking about the fact that this has changed their workflow. They're still feature gaps, they're still young, it's not perfect, but for example, like Duffel, this travel API company was one of our early customers and they would talk about how this was just such a big shift from manual painful work to now something that was much more automated. I think those are the early signs of product market fit. The CEO Figma actually said another very good sign of product market fit is when your customers start asking you for more, more product, new features that they're giving you, they want more of what you're selling them and that's also another interesting sign of product market fit. But for me, I don't think you, I think even when you're at like that 20 or 30 customers, it still feels tenuous as to whether you've like really cracked something that can become a big business. I would say you're still pre-product market fit at that stage, today, at 100 plus customers in the business where we understand exactly what we're selling, we understand where we fit adoption parts are smooth, time to value is measurable and fast and customers give you great feedback and love what you're doing. I think that is much closer to being at that product market fit point, but I honestly think it's a continuous evolution, anyone who tells you, even the companies at Series C and Series D and beyond are like, yeah, yeah, we found a perfect product market fit. You are always evolving your company. You need to find product market fit in new segments that you're going to drive growth with them. I think to you talking about staying true to your lane, to your product, to your original vision and customers, that hits home with me because my younger brothers also founder have seen him through similar cycles and he had to make similar tough decisions and so I'm wondering, did you go through any major product pivot in your journey and if so, how did you navigate those decisions, especially if you've found some level of product market fit or if you've already started seeing some revenue? Yeah, we pivoted our product in the early days and it was really largely a function of us having a hypothesis about a market building something, having some early traction but seeing a much stronger opportunity and customer feedback based on the product that we're building today, I guess having built a company before, you have a strong intuition as a founder about whether what you're doing actually has that ability to enable you to build the billion dollar business that you're trying to build. I built a small to mid size business before and I exited that, that's not what I wanted to do here. I wanted to go and build like a generational company and when I saw that it wasn't going to be the first thing that I was doing, we made the decision pretty quickly to pivot the business and I think one thing people don't appreciate is you not only have to pivot the business but actually like you have to pivot sometimes the shape of your team because actually the thing that you're doing is different and you need a different mix of skills, you need to pivot so much by the way that you operate and in the moment it's hard to do that because you have attachment and commitment to what was there before and it's also really hard to do because you have accountability to investors who are waiting on you to deliver them revenue and growth and so all in all, I do think it's hard to do but the reality is I think when you look at most companies, there are very few businesses that I know today that didn't like that started with an idea and that's the idea like that they're building with today. Like I'm sure if you go and ask like Alia Data Bros, anyone else, you know, guy, you know, anyone who who is, you know, built a sort of generational company like on the very first pitch deck you wrote or like on the very first idea you had is like this exactly how you envisage it and really honestly the answer is probably no because when you're actually trying to sell something in market, you only then do really garner like true insight from customers about whether or not this will work and you learn other things as well. I think the founder of Vanta speaks about this very well, I think she was trying to build a different product and actually whilst doing that, one of the like challenges I think she saw was that a lot of startup CEOs like couldn't access an enterprise segment because that, you know, the path to get it, you know, the path to getting kind of sock too certified was so cumbersome, almost like designed to block the segment out, that was like a counterintuitive thing that she learned whilst trying to build something else, obviously the Slack team are the same. They were they were building something and then using a version of Slack that they built for their own internal messaging and then realized that actually that was the bigger product opportunity for them and so I think this is generally considered to be a very not only acceptable, but like almost expected part of venture that I actually think USVCs have much more tolerance for than what I've seen kind of with European VCs where in European VCs, I think generally maybe kind of maybe don't work generalization here, but I've seen less appetite for that kind of change. I think it drives more discomfort. I'm sure that whole journey of navigating those difficult decisions has been very worthwhile, which reminds me, you've just closed your Series A, so massive congratulations to you and the team. We'd love to hear what story or insight resonated the most with investors during the process, but I guess some of your key takeaways from fundraising and from an investor's storytelling perspective. Yeah, so we have just closed a Series A and really excited 20 million round to take us to the next level as a company. The fundraising process, I actually personally really enjoy fundraising processes. I mean, they're pretty grueling, but the truth is it's a great opportunity to step back and look at your business and the summation of what you've built and think about not only how to tell that story, but also where you want to invest for the next chapter because when you're in the day to day of running the business, you don't often force yourself to go to that altitude and think about the next phase. So from that perspective, I think it's actually a really meaningful part of building a company that is very valuable. In terms of what resonated, one is that we've won some of the leading logos in the next generation of software businesses, Incident.io, LaGora, Bridge, MoonPay, Cognition, Rosbury AI, some like really leading SaaS and AI logos, and that's with a very lean team and really only being in market sort of 12 to 15 months. I think logo quality really matters because it's not only a test of building a great product, but also great logos attract more great logos. The other piece that's really a compelling part of our stories that we have 190% NRR, and that basically means that not only do we retain our customers, but we also see a lot of growth within our customers on our platform. So customers using more and more sequences, they scale, and again, that's a very powerful thing. Attention is not something to be underestimated, like top line matters, but today you have some great companies from a top line perspective that are turning half or 80% of their user base. And I think we saw some investors put a very strong onus on the fact that this is a really attentive product, and that the user love is clear when customers are adopting more and more of your product suite as you grow with them. And then I think outside of that our vision to become a category leader in this space and the real opportunity for disruption where there's this gap between where legacy incumbents are playing and really sort of a lack of let's say next generation leaders in this side. And ultimately, I think still at Series A, people are making a bet on you and the quality of your team and the approach that you have to talent. Can you bring in excellent people? Do you know what good looks like to ultimately scale this company? And so lots of different things, but I think those are some of the things that resonated most. I was speaking to another founder friend who basically said, when we get to Series A, the only thing that anyone cares about is your ARR, but the moment you scale beyond that, people care about your attention. So I'm very glad to hear that you have a better matters more than anything else. And I think everybody knows that. And today I think the market expects not only an amount of a certain amount of AR, but also like this, obviously, the speed of growth with which you get there. And VCs are looking for, have you been able to achieve some breakout trajectory and have a belief in the continuation of that breakout trajectory? And so definitely your top line matter. But then there's a lot of great companies being built with great top line. So how do you then make a compelling narrative beyond that? And then some of these other points matter. And another piece also is that a lot of investors spoke to our customers and think our customers had great things to say, could really articulate how we compare to the competition, why they love using our product. And again, I think that's a really, really important component of a successful fundraise. A lot of our listeners, as you can imagine, are either entrepreneurs or aspiring entrepreneurs. We would love to get your advice for them in terms of raising in today's AI heavy, but very cautious VC environment. Yeah, it's more competitive to build a company successfully today than ever before. The bar to creating an MVP, to expressing and articulating our idea is just lower than ever before, which is actually great because it's going to drive a ton of entrepreneurial ism. But you know, a lot of investors say like, really have like 10 or 100 X, the number of decks on that desk, particularly at Seat Stage, where nothing is really proven yet. And so I do think standing out matters, and of course, idea quality matters. But again, at Seat Stage, it's hard to really know whether something is going to work. And so your team and you as a person, and why you're someone to bet on, if the first idea doesn't work out, are you going to be somebody that sees this through? And that comes in all shapes and sizes. There's no like conventional profile for that. Like if you're somebody who believes you have the grit and tenacity to build something, it means that you're probably going to out-succeed most people who try and do this. And that's a really important trait. But yeah, I think back to your question, it is an extremely competitive landscape. And there is a lot of capital around for sure. And also there's a lot of opportunity, right? Like every incumbent category, it definitely will be disrupted with AI, whether it's trucks or robotics labs or microbiomes or enterprise software or how you book, travel. A lot of them do a such a meaningful technological shift that if honest well, you can build an insanely like strong company and truly disrupt, have a product offering that is so distinct from what was there before. And those kinds of seismic shifts don't come around often, you know, like when we moved from home on a parameter cloud, like a whole wave of new companies were built that just completely meant the sort of loss wave fell away. This shift is even bigger than that. At the infrastructure layer, at the application layer, hardware, software, consumer, like every single segment, probably hard to compete at the infrastructure layer right now, unless you're, you know, you have the appetite and the stomach to raise, you know, tens of billions of dollars to do it. But certainly at the application layer, I think there's so much to do. And so generally, there's been, there's no better time to build something. But there is so much noise in the market and cutting through is just more challenging than ever before. 15 years ago, if you had a great idea and you came from a credible background as many of your listeners are, don't it's easily, but you could go and raise capital from a top-tier venture fund. Today that is just harder because there are so many people competing for that. But at the same time, there is more opportunity than ever before. So I think it's a great time to be an entrepreneur. I think like the battle for talent is, is insane. There is also more exceptional talent being produced by virtue of like so many companies being built. But I think certainly like, you know, if you're looking to, you know, to hire engineers in Silicon Valley, I think about everything as being a sales process, like you have to have a really compelling narrative, not just a VCs to raise capital, but as to why like great people should come and join you and that will be the single determining factor between whether you're successful or not or how successful you are. Looking back on your journey, I'm sure you yourself have also grown as a CEO in many ways. Now we have a million more things to do at hand. How do you personally stay close to your customer's pain point? I think it's one of the most important things for a CEO to do regardless of the stage. And again, like I think some of the best founders in the world who have tens of thousands of employees and, you know, are global unicorn businesses, decor corn businesses are still very close to their customers. And how does that happen practically? I mean, like we have Slack channels with all of our customers. We see customer feedback. I joined some customer calls. I speak to a lot of our partners, you know, it's very easy to kind of hand that off entirely to sales teams as they grow, but, you know, every, like every week, I should be on at least a couple of customer calls, it's, it's really important. And I think that's one source of kind of customer proximity. The other piece is also just being very firmly embedded in the market. So go to conferences, you know, speaking on panels with some of our partners, like understanding the market narrative as well. And ultimately, like if you want to be successful in building into the right product vision, you need to really marry those two things. You need to understand at the lowest level what your customers are saying, but also understand like where the market pull is and what you, you know, what you're not envisaging yet, what your customers aren't saying, but what, you know, they might actually want. And so I think you need to, again, it comes back to sort of going high and low. Like you need to, you need to be, you can't be low in the details all of the time because it means you're not doing your job as a CEO, being able to step back and understand where you need to take things. But if you are too out of the wheat, I think you're more likely to be unsuccessful because really there's, it is those low level things that customers say that actually give you the deepest insight about your product and where your opportunities lie. And one great, like tactical way to do it is, you know, my dashboard is our CRM. So every day I'm looking at, you know, what deals are on and we record all of our calls in the business and, and so that's visible across the company and I will very often go back into sales calls and listen in when I'm curious on what's happening with a particular customer. And again, just as much as possible, see that voice of the customer firsthand. The other thing we do is we have an all hands that we run by weekly and we'll play back a lot of customer clips as well to the wider team because for me, it's not just important that I'm, you know, understanding what our customers want and need, but also that every single member of our team, regardless of the team are in, are doing that. It's very interesting to hear that it's permeates through the culture as a whole at sequence. We're almost at the end of our time, but before I let you go, I have to ask, what's next for sequence? Any upcoming products, features or directions you are particularly excited about? Yeah, I'm 26 is going to be a really big year for us. We talked a little bit about our agentic vision, but much more embedding of agents across this workflow, you know, we talked about the invoice review agent. We're going to have a dining agent, which helps manage cash collection reconciliation agent or reconcile contractions when they come in. And this is going to be a very like natural part of the workflow within sequence with kind of human and agent working together. And so that's a really big piece of our roadmap. Second is we're selling into larger and larger companies and more workflow configuration and customizability to allow us to capture that enterprise opportunity is a big part of our app pillar for us as well. And then ultimately we're scaling super quickly and probably going to be to re-ex the customer account over the next year, us figuring out how to lay the right platform foundations, but also team foundations to actually be able to achieve that is that it's really big. So we're hiring across a number of roles in the business, but it's not just about adding headcount, you know, we'll also like need to think, rethink some of the fundamental ways in which we work as a team. And what I will say is that's really what I love about building a company that you're constantly having to reinvent yourself every three months or every six months. If you just stay kind of static, you're, you know, you're never going to scale efficiently or effectively. And I think that's what makes this job really fun. It's been great to have you on the podcast, Rhea. I personally learned a lot. I hope you had a great time as well. I did. Thank you so much for having me young. And if anyone wants to reach out, Rhea, R-I-Y-A at Sequence HQ.com.