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Glasswing Ventures, which invests in enterprise companies, is operating out of a $112M fund
Venture capital used to be a cottage industry, with very few investing in tomorrow's products and services. Oh, how times have changed!
While there are more startups than ever, there's also more money chasing them. In this series, we look at the new (or relatively new) VCs in the early stages: seed and Series A.
But just who are these funds and venture capitalists that run them? What kinds of investments do they like making, and how do they see themselves in the VC landscape?
We're highlighting key members of the community to find out.
Rudina Seseri is Founder and Managing Partner at Glasswing Ventures.
With over 17 years of investing and transactional experience, Seseri has led technology investments and acquisitions in startup companies in enterprise SaaS, IT software and data, marketing technologies and robotics. Her portfolio of investments include Celtra, CHAOSSEARCH, CrowdTwist, Inrupt, Plannuh, SocialFlow, Talla, Verusen, and Zylotech. Seseri is a Harvard Business School Rock Venture Capital Partner and Entrepreneur-In-Residence, serving for 5 consecutive years. She is also a Member of the Business Leadership Council of Wellesley College.
Seseri serves as a member of the advisory board for GSK Consumer and the Philanthropy Board for Boston Children’s Hospital. She has been named a 2017 Boston Business Journal Power 50: Newsmaker, a 2014 Women to Watch honoree by Mass High Tech and a 2011 Boston Business Journal 40-under-40 honoree for her professional accomplishments and community involvement. She graduated magna cum laude from Wellesley College with a BA in Economics and International Relations and with an MBA from the Harvard Business School (HBS). She is a member of Phi Beta Kappa and Omicron Delta Epsilon honor societies.
VatorNews: What is your investment philosophy or methodology?
Rudina Seseri: Glasswing was formed in 2016 and we were one of the earliest firms, if not the earliest on the East Coast, formed on the premise that there was a new wave of AI and frontier technologies that was permeating the enterprise, cybersecurity, and platforms in general. Our view was, and remains, that there was a real opportunity to have a firm fully specialized in that, in large part because the East Coast has a heavy focus on enterprise and a lot of high quality enterprise talent, but also because the quantity of high quality deals is quite great, while the available capital in the market for early stage was lacking. Between the strategic focus on enterprise and cybersecurity, with AI as the driver for the paradigm shift, and the need for early stage capital, we thought it was a great opportunity to launch Glasswing Ventures.
Glasswing was founded by myself and my co-founder Rick Grinnell, and we brought in our third partner, Sarah Fay. Today we are a team of eight, investing out of a fund of $112 million.
VN: What’s the opportunity you see with AI in the enterprise?
RS: From a driver’s perspective, I think of AI as a layer that permeates across any end market. By the way, we're talking about narrow AI, where intelligence is the "what," definitionally, and machine learning is the "how." So, think of AI as a layer that cuts across any kind of end market and vertical. We see it in our daily lives on the consumer side, where it’s largely dominated by the incumbents - the Googles, Amazons and Ubers of the world. On the enterprise side, we are in the early innings of leveraging artificial intelligence to create what I would call the “intelligent enterprise.” It manifests itself in every facet, from leveraging predictives to delivering intelligence in marketing and sales organizations. So, it’s not just about analytics; it’s about predicting what will happen and also leveraging software that’s learning on an ongoing basis from the input to further drive performance, all the way to document protection.
The definition of the intelligent enterprise will be a place where we see higher productivity, higher creativity, where we take advantage of the consumerization of the enterprise, i.e. user or employee driven adoption of tech. Fundamentally, it’s about better performance and taking advantage of the new dynamics between employees, shareholders and regulatory bodies. AI also means interesting opportunities for end to end solutions in the vertical market, and the ever changing dynamics around the cloud and multi-cloud environments, creating opportunities around what we can do, not just around the infrastructure bid but all along the tech stack, from infrastructure middleware and apps to computing at the edge. We would never have been able to have this sort of conversation, or these kind of drivers, were it not for the computing power and the declining costs; (Moore’s Law is still holding). We wouldn’t be able to be in this paradigm if not for what happened around neural nets, particularly around deep learning, and the ongoing breakthroughs we are currently having. And of course the data that’s becoming available. It’s not just about quantity of data, it’s about the quality and veracity and diversity of the data.
VN: What are the verticals you like to invest in within the enterprise?
RS: There are a number of verticals that we evaluate. Right now we’ve made a bet in the supply chain management vertical with a company called Verusen, and in that instance it’s about taking a relatively old industry, with very little tech adoption, and leveraging AI and machine learning to have better predictive non-production inventory parts management. So, again, think of it is as trying to provide an end to end solution.
I would be careful not to categorize the fund as a vertical strategy fund, because we will also go after platforms where, by leveraging AI you can actually cause positive disruption. For example, for the AI paradigm to come fully into fruition, data is a key factor. We’ve made an investment in a company called CHAOSSEARCH, which I think of it as a data infrastructure play. By infrastructure I don’t mean hardware, it’s actually a software play, but it’s a fundamental solution; they’re enabling enterprises to take data that’s stored in cold storage, meaning data that’s stored but you cannot mine or access it easily, so it sometimes takes multiple days to even get to the data, and they make it queryable - they turn it into a database. They do so for a fraction of the cost of having it stored in hot storage, and at 6x the speed. Said differently, they make it very easy for enterprises to now store and mine and have access to orders of magnitude higher of data, but at a fraction of what it would normally cost them. That opens the whole door of fundamental tech - a whole new opportunity around creating new apps, and leveraging AI and machine learning to deliver at value. One of the biggest components is now a lot more effective and affordable. In this case, CHAOSSEARCH is not a vertical solution, it’s actually a data infrastructure play, so it’s horizontal.
VN: How many investments do you typically make in a year?
RS: I’m not sure that we start the year off saying, "This year we’re going to make X number of investments." There are times when I’ll make two investments in a quarter because the opportunities that emerged happen to be strong; there are times when I won’t make any investments in any given quarter, and I think the same holds true for my partners. It has turned out to be four to five investments a year but, I would be careful not reading too much into that. For us, it’s about sticking to our strategy and being thoughtful and going deep and adding value in the investments we make. It’s not about a certain pace. We’re experienced VCs, and we know we have a five year horizon. We know what it means to invest in year one versus year four, but, at the end of the day, we’re looking to back the best founders with the best execution, “chops” and vision who will build the biggest companies.
VN: What stage/series do you invest in and how much is that in dollar amount for you?
RS: As I’m sure you’re well aware, the nomenclature has shifted a bit. Today, what we call the seed stage used to be the Series A, and what we used to call the seed is now the pre-seed. So, I’m always wary of labels because I don’t want form to take over for substance.
I’ll answer the question by saying we tend to be the first capital, so we’re writing that first $1.5 to $3 million check. Unless we are incubating a company, which we will do from time to time, we typically like to co-invest in all of our deals. So, again, we’re writing that $1.5 millon out of a $3 or $4 million raise, or $3 million check out of a $6 or $7 million raise. And it typically gets labeled as a seed, and sometimes A, but, from a maturity perspective, it’s a point where the core team is in place, there is some product and there are early the indicators of product market fit. This is 95 percent of the capital; we also will go earlier stage and (which accounts for three to five percent of the capital) make pre-seed investments, or the old seed. These are instances where we see exceptional founders going after just phenomenal markets and, even though some of the proof points might not be all there, we’re making a bet on the founders, their vision and what we perceive their execution ability to be.
VN: What kind of traction does a startup need for you to invest? Do you have any specific numbers?
RS: It’s too early, so the answer’s no. We don't have the Series A mindset of, "I’m looking for $1 million plus in ARR." What I am looking for, though, are the early indicators of product market fit, and it’d be dangerous to tie that to a certain dollar figure. Not because I don’t like revenue, quite the contrary, but, in certain businesses, revenue follows the product. When you have deep tech the product may take longer, and in other businesses you see revenue instantaneously. So, I’m looking to see if they have some pilot customers. Do they have some early user adoption? They may have done it for free, for example, with a freemium model but, once it’s put into the user’s hands, the usability, the active user numbers, are off the charts. So, I’m not married to a particular number, but I am married to the notion of traction. How do you de-risk for product market fit? It’s not fully solved but there is some de-risking that has taken place.
VN: Is the traction you're looking for any different because you’re investing in enterprise rather than B2C companies?
RS: The traditional school of thinking tells you consumer companies look for new users, active users and that kind of adoption, and then revenue and the revenue model follows. In enterprise, in the early days you’re looking for meaningful logos, and there’s a difference if it’s a small enterprise versus a Fortune 500. Also, how deeply are you integrated into that play? What does the customer think? Are the dollars immediately large or not? Also, when I say enterprise, it’s not to be confused with the sales cycle of a year plus; some businesses do have that, but, for the most part, the sales cycles are much shorter. So, we would take all of that into account.
VN: What other signals do you look for? Team, product, macro market?
RS: It’s the people. Nobody should be surprised that people make a difference, whether you’re in the venture business, looking to back a team, if you're a company yourself or whether you’re looking at who you're hiring. That is the number one focus. Having said that, what we look for in people is the ability to both have execution and vision. If you notice, I’m leaving the phrase "big idea" out of that answer, not because I’m not looking for a big idea but because I’m casting it as a vision which, in my view, is not just about the idea but the maturity of perceiving what the business can become in the context of what markets you are going after. Vision without ability to execute is limiting, so we look for teams where execution ability and vision are there.
Another criteria is that we look for a different type of construct. If, historically, let’s say for a new software company you have the technical co-founder and the business co-founder, when you take advantage of AI and machine learning, there is a third leg to that stool which is very specific to AI native startups, and that’s the Head of Data Science or the Head Machine Learning, or however that individual manifests themselves in the context of a startup. It’s a new phenomenon, so the titles can be all over the map. If you think about it, to really take advantage of AI and machine learning, you have to basically incorporate the neural net into the algorithms from day one. So, what’s the dynamic between the tech/product leads and the data science lead? There is this new dynamic in the team and that has ramifications around how product decisions get made.
VN: Are you seeing more teams now with someone in charge of AI and machine learning?
RS: For the most part, they typically will have someone on the team, sometimes that person is very senior, sometimes they’re junior, sometimes they’re looking for someone else. Because we see this day and day out, we also have an advantage in doing diligence in that regard, and in helping them with talent. At Glasswing, we have a group of over 30 advisers, a big subset of who have AI and machine learning domain expertise, and who work with us closely and exclusively - from diligence to sourcing - to helping us recruit for talent. In this day and age, there's still a shortage, so access to that kind of talent is a big differentiator.
Recently, we announced that Vlad Sejnoha has joined us as a venture partner; Vlad was the CTO and SVP of R&D and tech globally at Nuance, which is a deep AI and speech recognition platform, for many, many years. Prior to that, he was also chief scientist at Kurzweil AI. So, we live and breathe the space and we have the domain expertise in-house and throughout our advisers. I mentioned that because it’s one of our points of differentiation, not the only one but an important one.
VN: Do you think about valuations when you invest? Or is it too early at that stage?
RS: Any experienced VC thinks about valuations because it has ramifications around outcomes and portfolio construction, so absolutely we do. We have seen upwards pressures in valuations, and we still, at the early stages that we invest in, have between 10 and 20 percent ownership in our portfolio companies; ownership is important, especially in the early stage. And we maintain abundant reserves for follow-on rounds to be able to maintain that ownership, especially for companies that are outperforming.
I do think that the upward pressure on valuations on the East Coast is different than what you see on the West Coast, simply because there are so many more VCs on the West Coast and there’s so much more capital concentration. It is a lot easier to view capital as a commodity on the West Coast. We’re not immune, but I think it’s less the case on the East Coast, where there’s an abundance of opportunities in terms of entrepreneurs. So, we don’t have as much of a challenge of too many VCs chasing the same deal, though there is plenty of healthy competition.
VN: There are many venture funds out there today, how do you differentiate yourself to limited partners?
RS: It’s interesting that you ask about differentiation from an LP perspective; oftentimes I think about how I differentiate myself from a founder’s perspective. Not only is it about why should I provide capital to them, but why should they take our capital? How do we add value for them? I raise that because I think differentiation starts there.
Everything about Glasswing is founders first, so it’s not just about the capital. I’ll share my own mantra: when I’m thinking any company or any founder in my portfolio, my first instinct is, “What have I done for them lately?” more than what I will expect from them in return. This should be an indication of how we approach it; we view ourselves as extensions of the team. They’re early stage, so this is not about the high and mighty VC coming into the board meetings, doing calls every so often and then saying, “I’ll see you the next time.” This is about how we can help them hire their first Head of Sales. How do we help them hire or beef up the tech team or the data science team? How do we help them find their first few customers? There have been a number of instances where we weren’t the highest bidder but, in real time, during diligence, closed customers for what became a portfolio company. We also think of Glasswing as a platform, which is that we support our companies, not only with our knowledge, not only with the years of experience we bring to the table, but with truly scaled approaches to recruiting, to share services, to support in infrastructure and operations and, more importantly, to revenue generation and helping companies get customers to strategic direction as well as the ability for founders to connect with each other and raise future rounds. We also know that founders need room so we’re direct, we’re trustworthy and we let them run their companies. We step in when they need us to step in, not when we think we should step in, and that’s an important differentiation.
Coming back to the LP question, all of that, and making the right investments in the right founders, married with the Glasswing platform, means that the outcomes are strong. If you look at all the funds that have been raised recently, say in the last three to five years, at least on the East Coast, we raised one of the largest first early stage funds at $112 million, and I think that’s because we had a track record of performance and because the founders truly stepped up for us and indicated to the LPs what we were made of. The LPs will talk to the founders and look at the inputs but, at the end of the day, the first screen is what performance have we generated, and, while I can’t go into performance, it is no accident that we are fully institutionally backed fund.
To put a bow around our key differentiators: one, we put founders first; two, Glasswing is a platform, so once they come into the family the whole platform works for them; and, three, the proof is in the pudding. So, it’s really about how differentiated our strategy is and how we approach our founders but also our view of our market around AI and machine learning. Again, it was no accident that we were one of the earliest AI-focused funds because we go deep into our thematic work and deep into our thesis to develop a view, and then go execute on that basis.
VN: What are some of the investments you’ve made that you're super excited about? Why did you want to invest in those companies?
RS: In any company I’m looking for budget, for vision, for a big market and to see that they’re solving a big pain point.
We have a portfolio company called Talla, which is solving the problem of customer success and sales success teams, helping them drive incremental sales and also drive support challenges, especially if they’re working off of a set of questions and answers, which may or may not be what the customer on the other side is looking for. What Talla is doing is actually deliver an automation platform where they’re leveraging natural language understanding to address those questions as a first module, as a first go to market, i.e. to help empower the worker, in this case the customer success person, to address the question that may or may not be in their FAQs by typing it exactly as the customer is posing it. Then, whether it’s in the FAQ or whether they have to use Talla’s platform, the tool goes and does a search across the knowledge base and, because it understands the question, it can deliver highly relevant answers. From there, it can actually deliver predictives and make strategic recommendations around what the customers may or may not need as part of what’s being sold to them and how it’s being sold. That’s just a first step; you can apply that to IT, you can apply that to the HR space.
The founder Rob May, is an exceptional evangelist and execution minded person. Not only is he a repeat successful entrepreneur, having previously built and sold Backupify, but he’s a thought leader in AI. His co-founder, Byron Galbraith, brings deep, deep expertise around natural language understanding and machine learning in general; he came out of academia but with an entrepreneurial bend. Then the Head of Technology, Paula Long, is second to none; she was the co-founder EqualLogic, which sold in one of the largest all-cash transactions in history, in the billions. It’s an exceptional team, with exceptional execution abilities, going after a real problem with real budgets.
VN: What are some lessons you learned?
RS: I’m in my fourteenth year of being a VC, and my co-founder has been a VC for 17 years. Glasswing is a new entity, but there is nothing new about our strategy, other than we’re taking advantage of AI, which is the current driver for the paradigm shift. As other frontier technologies emerge, we’ll focus on those. Venture is what I’ve lived and breathed for many years. Prior to being a VC I was at Microsoft at their corporate development group, and prior to that I was at Harvard Business School and on Wall Street and Wesley College. So that’s my quick bio.
What I’ve learned is the importance of passion for innovation, tech, transformation, change in general. How do you drive change by leveraging innovation? That has to be a constant, that has to be a deeply rooted passion, because that drives curiosity, that drives the desire to be constantly learning and evolving as teams and market dynamics evolve. Second, as you work with founders, you gain a deep respect for what they are doing. Think about it: waking up in the morning and saying, "I’m going to start a company," knowing that, by any measure, the odds are set against you, and yet still doing it. As an entrepreneur and founder myself, I have a deep, deep respect for founders, which I’ve always had, but it’s at a much higher level now, having gone through that journey myself.
Largely, my approach is to be direct and honest with founders, rather than saying, "Oh, you’re so great and I’ll never invest in you." Startups are hard enough, candor is an important differentiator and I’ve always stayed true to myself for that. Having said that, I think it’s also important to understand that, even when you put in the capital and you take the board seat, it’s a role of influence. Don’t dictate, but try to influence by adding value.
VN: What excites you the most about your position as VC?
RS: It goes back to the first part of my answer to the last question, which is the desire for innovation, the passion for tech and transformation and innovation. I’m fairly young but I still say it keeps me at 20 because being around these young founders keeps me current, keeps me hungry, and keeps me curious. It literally has a direct impact on me. You have high highs and low lows, invariably, but it’s my desire to be part of a transformational journey and that is something I’ll never get anywhere else, and I get to do so with amazing people.
VN: Is there anything else that you think I should know about you or the firm or your thoughts about the venture industry in general?
RS: I touched on this, but only passingly: the role that Glasswing is playing in the ecosystem on the East Coast, how involved we are, and the reach of the Glasswing platform. It’s important to us to contribute to the ecosystem, whether we’re investing in a particular founder or not, paying it forward and doing the right thing goes a long way, both in building relationships but also in having a vibrant ecosystem. We really subscribe to that philosophy.
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