Collective[i]: Leveraging Artificial Intelligence to Analyze Decision Making, Influence Go-To-Market Strategy, and Bring B2B Sales Organizations Into the 21st Century

While CRM platforms have been a cornerstone of the sales industry for decades, many parts of the B2B sales playbook can still reflect decision-making from decades past. Whether it’s faulty data capture, cumbersome manual data entry, or inefficient forecasting, the digital revolution has yet to fully transform B2B sales organizations away from their traditional, intuition-based operating practices. While following the tried-and-true sales strategies may yield modest success, leveraging AI-powered sales data allows sales organizations the opportunity to better understand their buyers, cut down on time spent attempting to predict the future, and close deals as a team that might have otherwise been left in the pipeline.

In this episode of Growth Hacks, Kunal and Katja are joined by Stephen Messer, the founder of Collective[i], a leader in AI-enabled digital sales and customer relationship management. Stephen walks the group through some of the biggest learnings he and his team have seen on Collective[i]’s data-powered platform, and how they can be used to relieve many of the pain points he continues to see B2B sales organizations struggle with. He breaks down how decision making has shifted in recent years, and what sales teams can do to better service these new spheres of influence and walks the team through some of the biggest myths he sees persisting in modern B2B sales today.

Here’s what you’ll learn:

  • Why companies are still wasting time on ineffective forecasting, and ways to do it better
  • How the sphere of influence in purchasing decisions has grown to involve larger networks
  • Ways that AI can help sales teams to better understand buying decisions and optimize go-to-market strategy
  • Why Stephen is bullish on sales organizations changing their operational playbooks as the industry further digitizes

To hear more on this, settle in and press play. 

Please find the transcript below, which has been edited for brevity and clarity.

Kunal: It is a real pleasure to introduce you to today’s guest. He’s many things, among them an entrepreneur, a founder, attorney, patent holder, professor at Columbia, angel investor, winner of a ton of awards, brother, son. Please welcome Stephen Messer, who’s the founder of Collective[i], which is a leader in AI-enabled digital sales. This company has seen thousands of opportunities run across its platform and today Stephen’s going to share insight that no one company could get on their own. We’re to go through those today. Welcome, Stephen.

Stephen: Thank you so much. It’s great to be here.

Katja: Great, Stephen. Where does this podcast find you today?

Stephen: Today I am in the beautiful Saint Kitts in the Caribbean.

Katja: Awesome. That’s quite the location. As we start the new year, we are really excited about bringing you a different flow for today’s episode. We’re actually partnering with Collective[i] to share the top 10 takeaways based on the enormous amount of data that they gather on their platform. So, Stephen, let’s start with number one, Salesforce activity. How much of it is actually recorded in Salesforce?

Stephen: This is a crazy statistic. When you look today, there’s probably less than 16% of the activities that a sales professional does is mapped into the CRM. Now, that by the way also ignores all the contexts that usually are supposed to be put in, but don’t get in as well. We have a product called Intelligent WriteBack and the goal of that product is actually to find what’s really going on and the reason that CRM is so dependent on getting an accurate and complete view of what the seller is doing every day to help them improve.

Kunal: Stephen, I know when we run those assessments, even in our own companies, that 16% almost has a plus or minus of one, so it is truly a solid stat on what the activity of the reps are. Just imagine if we were a contestant on Wheel of Fortune — how many phrases would we get right if we could only see 16% of the letters?

Stephen: Yeah, you’d have to probably hope for a two-letter word for you to be able to figure it out. If it is a normal phrase, you would probably be looking at this saying there’s no chance. I think that’s exactly what’s happening in sales orgs today that are looking at their data.

Katja: Wow, that’s astounding. Moving on to number two, Steve, which is a popular topic with TCV as well, forecasting. How many hours does the average company spend on forecasting and how accurate has it been? And I want to hear your Marvel story.

Stephen: Yeah, forecasting is an interesting one. When you look at the statistics, whether it be from analysts or even from the data that we’ve seen, most organizations have historically spent about 20% of their time doing forecasting. So forecast Fridays are actually forecast Fridays. They spend the entire day. It’s kind of amazing to think that we give up 20% of selling, which is one day out of every week, to focus on a non-revenue producing task of forecasting. I find it even more crazy because it’s trying to do something that no one’s really been able to do in the history of the world, which is accurately predict some future event. No human on the planet has ever predicted the future. They’re giving up 20% of their time to get to an accuracy rate that’s almost been historically impossible to do.

When we look at that, we think to ourselves, okay, this is a real problem. And in fact, this is where my Marvel story comes in. I’m a comic book geek. I love them all. And in Marvel, there’s always a lot of themes around moving to the future and back and forth. But if you look at even the most recent Marvel movies, The Avengers, what you’ll see is that Doctor Strange saves humanity at the end of the movie by being able to go and live millions of lives to see which is the only way that they’ll be able to defeat the evil villain.

In this case, it’s pretty amazing. He gets it right. But two movies earlier before this evil villain even showed up, Doctor Strange is in a movie and could not predict that this person was coming to avoid it. In other words, even the superhero with the power to see the future has a 50-50 hit rate at best. What that tells us is that storyline worked because no one believes that anyone can predict the future. We think forecasting is going to go through a big revolution in AI and we’re excited to see people get 20% of their day back and more accurate up-to-date daily predictions.

Kunal: I love the Marvel story, Stephen. I think Marvel has like 7,000 characters and like two can predict the future, which just tells you how difficult it is to do. I know from a TCV perspective, we view forecasts. It’s like Kevlar for the board. When you have predictability, it makes spending the budget that’s allocated way easier. I think the forecast plays a critical role at all levels, but if you’re an operator in the company, you can find your budget being restricted if you start not to be predictable.

Stephen: And I think that’s really it. I think what boards want is the confidence in understanding what’s changing in the world. No one expects a sales professional at the start of the pandemic to predict exactly what’s going on. In fact, if you look at most of our competitors in forecasting, we were the only ones who hired up instead of laid off people because our AI was telling us that it was actually going to be a good thing, an accelerator for our business. I think companies like Zoom and some other players had a huge lift from the pandemic, so laying off people would’ve been putting the wrong brakes on and using people’s opinions probably wouldn’t have been the best way. But what they want to understand is how is the daily change affecting their likely future so they can decide, do I open up budget or do I close it down? They also want to make sure that they’re on track, that it’s reliable, that everything is predictable, and I think that’s really what forecasting with an AI product is all about.

Katja: That’s great. Sticking with superheroes, I always like the Lasso of Truth of Wonder Woman as well, which I think is something I would like to have.

Stephen: I think salespeople would like to have that with their customers as well.

Katja: I think so. Moving on to number three, one of my favorite topics, is the number of leads in people’s emails that never make it to marketing.

Stephen: It’s not just emails. It could be in their phone calls; it could be in their video conferences. I think the challenge around CRM has been the cost that it takes to enter information and the mundane nature of it. I did use to work with the UN and I used to joke around and say the only thing the Geneva Conventions didn’t cover was making intelligent people do manual data entry into databases. It’s cruel, it’s hard, and that’s why a lot of salespeople tend not to put that information into the CRM, even though it’s some of the most critical data that they need. When we think about that today, what you end up with is maybe one or two contacts entering into the CRM when in reality, seven to eight buyers are involved in the transaction and that sales team, and the marketing teams have no idea about those other people.

Kunal: Yeah, what we’ve seen, and I think what we’ve heard in the past is roughly 70% of the people we work with on an opportunity just never make it into Salesforce. and I think you’re validating that with the data you’re seeing as well.

Stephen: Yeah, we’ve seen it in your portfolio, right? It’s amazing how many names get uncovered that are involved and it changes the way you think about how the buyer is going through their buying process. That can give real advantage if you know who’s there. Take for example account-based marketing, a very popular new form of doing personalized marketing communications. Well, if you never know who’s there and you don’t know the personas, you’re not going to be able to get that marketing tailwind from your organization simply because you can’t get that information into the CRM and put it in a way where it’s trustworthy.

Katja: That’s right, and that leads to our next topic. How do you then build a solid pipeline? Right? Because what we are seeing is that the majority of pipelines have really bad data; we see that these deals are in the pipeline that are over a year old. They have closed dates that have changed more than three times, but actually no activity in the last seven days and no change in stage in the last 30 days. What happens is usually half the pipeline falls out when we look at the health this way. What’s your fascinating pipeline stats, Stephen?

Stephen: I’m going to first highlight things that every sales leader who’s been around for the last decade knows. We used to talk about 2X pipeline coverage, then it became 3X and 4X and 5X pipeline coverage. It wasn’t that win rates were going down; it was that salespeople started warehousing more and more deals. When you don’t have visibility into the actual activities and contacts that the sales organization is interacting with, it’s easy to lose sight of which deals have just gone away that the seller doesn’t want to close. That can be as simple as loss aversion, or they want to hold onto it in the hope it comes back where they can get it again.

When you look at these pipelines, it’s actually causing real problems. Your CDR team doesn’t even know who to feed new deals to. It creates all these issues. The bigger issue is all the while they’re being warehoused, these opportunities are sitting there idle. There are no marketing messages going there, there’s no keeping up with the buyer who may no longer even be at the org. This is a real problem. What we see today is that sales professionals hold on to close lost deals for about three times longer than a closed deal.

Kunal: That’s a fascinating stat, and Katja and I have seen this over and over. We actually have a white paper on pipe dream versus pipeline that covers some of this as well.

Stephen: Yeah, it’s a great read and I recommend it for anyone who’s listening to this podcast.

Katja: Thank you. It’s definitely eye-opening what we’ve observed working with companies. Along those lines, we also see that almost 100% of companies assign leads based on territories. And they almost make no reference to connections, which feels like 1950s selling. What do you think, Steve?

Stephen: Look, I think sales is going through a huge revolution and a lot of the ways that all of us came up through sales leadership must be re-examined. When you think about territory management, that was designed for the traveling salesperson who carried a roll of dimes in their pocket, would carry their bag from location to location. So, it made sense that territories be fixated around where it was fastest for them to meet the most customers.

Well, that hasn’t existed since the ’50s. The world has changed. I would argue cell phones alone changed it but look what’s happened during the pandemic. People can work from anywhere. It’s easy enough to do business from anywhere thanks to modern day technology, but the biggest thing that we see today is that as people have access to social networks, they are leveraging their relationships to learn what other products other people are using, what works and what doesn’t work. The idea that companies aren’t countering that trend by leveraging relationships that exist in their org, just lying there as data not being used, we think is just sad because there’s a lot of opportunity for people to leverage their friends, their family, their past colleagues, their prior customers. All of this exists and it’s just sitting there to be taken advantage of.

Kunal: Outstanding. Most closed lost opportunities, they’re lost because of no decision, no actual competition involved, and this is code for we just never got buy-in. Maybe you can speak to the number of people you’re seeing involved in a deal as well as how you guys map out circle of influence here to measure, are these opportunities going to close, not close, et cetera?

Stephen: You can probably tell from my statements I really believe that the social world has moved from the consumer into the B2B. And we’ve known that when it comes to jobs around things like LinkedIn, but you’re now seeing it spread into the sales world. We have a product called Connectors that allows you to discover connections, both at your org, but amongst your friends and your family and prior colleagues, et cetera, because we think that’s the most important thing. Why? Well, today if you were to look at the number of buyers involved in a transaction, you’d see across our network that they’ve gone up every single year. Now we’re not alone. All the analysts have been talking about this for a while, but what that means is a lot of the ways that we’ve historically sold, what we’re looking at now is that buyers are making decisions where they’re doing the research on the web first, they’re getting a lot of people involved. It’s a consensus-based purchase and they have their own model and methods of buying.

On the selling side, we’re seeing the same thing. There’s not just one seller anymore. We used to hold the salesperson accountable, but today we have to hold people like legal and finance, your joint venture partners or resellers accountable. What that means is you now have a lot more people involved. Well, the benefit of that is that they all have access to connections as well where they can leverage, and in fact, if the organization can start to learn that circle of influence, they can actually work in conjunction with that buying group to influence everybody involved. It’s a pretty powerful world when all these social connections are working together.

Kunal: I totally agree, Stephen, and one interesting thing that we see that you guys have patterned out is you would take the win rates and you would be able to pattern out kind of these next best set of actions based on what’s kind of moved the needle in the buying journey. Maybe you could talk a little bit about how you guys do that and what the impact has been.

Stephen: The funny part is AI has been popular in the consumer world over the last 20 years, really accelerating in the last 10 years as neural networks have spread through, and a lot of the things that we love so much about those B2C apps is how personalized and how effective they are. The way they do that is by leveraging large networks of data, right? Facebook, TikTok, et cetera. Well, those same exact technologies are being applied now into the B2B world, and in particular B2B sales. We use all these technologies and a large data set to help us find out how does each buying group make their buying decisions? If I can observe that same buying group across multiple sellers, it allows us to really start making good predictions about when they do this, what it means or what they’re going to do next. Then we can look across an even larger network to start to understand what people do that lead to certain win or losses.

The cool part about AI is you can run the time forward, which is, okay, here is the stack pattern of what we’ve had today. What’s the optimal thing you can do next? We can suggest that and just like all apps, take Waze for example, I don’t always have to take the optimal route if I don’t like the route, but the route they’re suggesting is probably going to be the fastest. If I take it, it’ll look at the activity. If something new happens, it’ll reroute it again. So, you’re always looking for, what’s the optimal way to work with this customer? In other words, how do I personalize my sale to the way this buying group likes to buy?


What I love about it is the fact that on a win, you can tell me the needle-moving actions that happen in aggregate even all the way to the industry level. I think it’s super precise, and on the flip side, I can take my losses and map out what is not moving the needle. So, again, it has the impact of making my go-to market strategy, just giving it more precision.

Stephen: You know what else is cool for sales organizations and sellers? It’s so personalized that it’s giving them their unique advantages served up to them on a plate. When they win that transaction because they had a great connection over at the org, that’s something that only they could have taken advantage of. It’s a really powerful way to get every bit of strength out of your organization.

Katja: Well, Stephen, we’ve covered a lot of myths. What’s one that surprised you in 2021?

Stephen: It’s a good question. the thing that most surprises me is this idea that we can still predict the future. The reason I say that is we’re sitting here locked at home at the point where all of us thought we were going back to the office. I just saw today that Apple has postponed indefinitely when they’re going to go back to office. This idea that rather than reacting to news quickly and having the optimal way of doing things, we’re still trying to predict the future. I feel like COVID has been the great lesson in the fact that as great as we think we are at making decisions, we’re not always great at predicting the future, but what we are amazing at is how we can react successfully to it.

The American economy and globally the economy is going strong because we all moved onto the web, and we all were able to make really fast changes in the way we historically operated. I think the thing that we’ve learned more than anything else and the biggest myth is that change can be hard. I’ve watched organizations that never had video conferencing switch overnight and operate globally on video conferencing within a span of weeks. I think we can change quickly.

Kunal: I agree, Steve. And when you have something come in so significant that forces you to change, you’re able to break through barriers way faster than you thought was humanly possible. I guess, as we kind of wrap up here, what’s one enduring myth you wish would just go away based on the data you’ve seen over the last 10 years?

Stephen: It’s a good question. If I were to pick one myth, I think the biggest myth is that the sales organizations are going to continue to just operate in the same way they’ve done over the last 30, 40 years. I think a lot of people are tweaking around the edges. I see this as a transition from being a very qualitative, very opinion-based world to a very quant heavy world. We saw 20 years ago the marketing world move from brand marketing to digital marketing, and while it might have seemed scary at the time, today they’re one of the most powerful parts of any organization where arguably years ago, they were considered to be tarot card readers. Today they’re core producers. I think sales will go through a huge transition as it digitizes, and that will change everything about how we operate for the better.

Katja: That’s awesome. Thank you so much, Steve. It was so nice to have you on the show. And some of the takeaways that I’ve picked up are throwing out the old playbooks and leverage AI as well as relationships and connections to get better at many things, including forecasting, lead generation, building a pipeline, and more. With the universe of buyers and their access to information increasing, we also see sales teams growing with more people involved in the process. Thanks for sharing your thoughts on how to increase win rates and pitfalls to avoid. And most importantly, how buyers and sellers can work together. Thanks so much for being with us today, Steve.


Thank you for having me on the show. It’s been fantastic.


Thanks for listening to Growth Hacks. You can follow us on Spotify, Apple Podcasts, or wherever you listen. To learn more about us and TCV’s CEO and founder podcast, go to or email us at


The views and opinions expressed are those of the speakers and do not necessarily reflect those of TCMI, Inc. or its affiliates (“TCV”). TCV has not verified the accuracy of any statements by the speakers and disclaims any responsibility therefor. This interview and blog post are not an offer to sell or the solicitation of an offer to purchase an interest in any private fund managed or sponsored by TCV or any of the securities of any company discussed. The TCV portfolio companies identified, if any, are not necessarily representative of all TCV investments, and no assumption should be made that the investments identified were or will be profitable. For a complete list of TCV investments, please visit For additional important disclaimers regarding this interview and blog post, please see “Informational Purposes Only” in the Terms of Use for TCV’s website, available at

Humu and TCV Partner on $60 Million in Series C Funding Round, Fueling Growth of Science-Based, AI-Powered Technology to Build High-Performing Teams and Managers

MOUNTAIN VIEW, Calif., Jan. 25, 2022 /PRNewswire/ — Humu, the HR technology company combining behavioral science and technology to help employees build better habits at work, today announced $60 million in Series C funding. The round was led by TCV, one of the world’s leading growth equity firms, with additional investors from Humu’s previous funding rounds including Index Ventures, IVP, and SVB Capital, and new investors Global Founders Capital and Blue Ivy Ventures. The investment will fuel new product innovations focused on supporting managers and their teams. TCV venture partner Jessica Neal, former Chief Talent Officer at Netflix, will join Humu’s Board of Directors as part of the partnership.

The investment follows 10x growth in users over the past two years. Humu, whose platform coaches managers and employees into developing work habits that are scientifically proven to drive performance, has emerged as the leading force in HR technology as companies evolve their people-management strategies in the new age of work. By nudging teams with short, science-backed recommendations, Humu provides personalized guidance that is unique to each employee and also aligned with company goals. With Humu, customers see improvements in retention, manager effectiveness, team performance, and inclusion.

“Humu, through technology and science, can help shift behavior in an organization,” said TCV Venture Partner Jessica Neal and board member at Humu. “Its ability to provide individualized support to employees and managers that can scale across an entire organization and drive outcomes that HR leaders care about is truly unique. Employees who are actively engaged with Humu have shown to be significantly less likely to leave their jobs, effectively lowering retention risks for companies. Feedback from customers is that Humu has become invaluable to their HR efforts. This is not generally the sentiment with HR technology.”

“As a firm that focuses on long-term value creation, TCV believes that Humu with its deep background in people analytics, has the potential to make a positive, and large, impact on the way we all work,” continued David Eichler, Partner at TCV.

With this latest round of funding, Humu will take steps towards executing its bold vision of making it easy for every organization to build a unique, high-performing culture, based on proven best practices. This vision, which includes manager-focused product developments and an expansion of Humu’s footprint within enterprise customers, will be fueled by hiring for roles within product development, commercial, and science teams.

“When we began this journey in 2017, we knew our experience in pioneering the field of people analytics would help us build the best technology for supporting managers and employees, and we’re proud of the impact we’ve made,” noted Humu CEO Laszlo Bock. “This latest investment, led by TCV, signals our partners’ confidence in our ability to deliver on that promise long into the future, and we’re excited for what we’ll bring to the market, especially for managers, in the months to come.”

As companies continue to navigate uncertainty and transform how (and where) work happens, employees will need more personalized, targeted support than ever. Managers in particular play an increasingly important role in connecting employees with the vision of the C-suite. According to data from Humu, teams are 80% more likely to make improvements when they see their manager taking action. And during the pandemic, employees with a manager who offered them personalized support and development opportunities were 7.9x more likely to stay at their jobs. But this added responsibility has left managers struggling to balance team workloads, boost performance, and combat burnout. Against this backdrop, Humu is enabling managers and employees to engage more quickly, honestly, and constructively, so that they can make work better for themselves and their teams.

By increasing its ability to support managers, Humu will further help companies improve team performance. Specifically, its platform pinpoints the most important habits managers and employees should develop to hit company goals, and then nudges teams into practicing those exact behaviors in their day-to-day work. By combining behavioral science best practices with technology, it empowers leaders to support their people in a way that’s modern and measurable.

Humu works with companies like Expedia Group, Kickstarter, and sweetgreen to deliver timely, personalized, and relevant coaching so that managers and employees can do their best work every day. For more information or to view open positions, visit

About Humu 
Humu is an action management platform that makes it easy for employees to improve, every single week. Science shows that the fastest path to improvement is via personalized coaching in the flow of work. That’s exactly what Humu does. Humu nudges managers and their teams to build the specific habits that will lead to their organization’s success. Unlike most tools, Humu combines Nobel-prize winning science and technology to pinpoint which behaviors and people skills leaders, managers, and employees need to be effective. Humu helps customers drive outcomes like improving managers, increasing agility, building more inclusive cultures and boosting team performance.

For more information about how Humu can help your employees, please visit

About TCV 
Founded in 1995, TCV was established with a clear vision: to capture opportunities in the technology market through a specialized and consistent focus on investing in high-growth companies. Since inception, the firm has built a track record of successfully backing private and public businesses that have developed into dominant industry players across internet, software, FinTech, and enterprise IT. TCV has invested over $16 billion to date, including $3 billion in fintech. TCV has helped guide CEOs through more than 145 IPOs and strategic acquisitions. TCV has invested in cutting edge technology companies including Airbnb, Brex, HireVue, Klarna, LinkedIn, Mambu, Miro, Mollie, Netflix, Payoneer, Peloton, Revolut, Trade Republic, Spotify, Wealthsimple, and more. TCV has successfully executed over 350 investments of varying structures, including mid-stage, late stage and public company investments, and has offices in Menlo Park, New York, and London. For more information about TCV, including a complete list of TCV investments, visit

Media Contact 
Sydney Perkins 
Mission North for Humu

Katja Gagen


BenchSci Raises $63 Million Series C to Solve Pharma’s Biggest R&D Challenges with AI-Powered Software Platform

Toronto, Canada, Jan. 24, 2022 (GLOBE NEWSWIRE) — BenchSci, a global leader in machine learning applications for novel medicine development, today announced a $63 million Series C (US $50 Million) funding round led by Inovia Capital and TCV, with participation from existing investors. 

Bringing total investment to $123 million (US $97 million), the funding allows BenchSci to expedite the expansion of its transformative AI-powered software platform that accelerates research in 16 top-20 pharmaceutical companies and over 4,500 leading research centers worldwide. 

Leveraging over 100 proprietary machine learning models, BenchSci’s platform empowers 49,000 scientists globally to optimize their experiment designs and hence research productivity. Building on the success of applications that help scientists select reagents and model systems, BenchSci is evolving its technology to provide a comprehensive platform with capabilities that help leading pharmaceutical companies solve their biggest R&D challenges.

“This funding demonstrates trust in our ability to build and deliver a next-generation AI solution that helps global pharmaceutical companies develop novel medicines faster, ” says Liran Belenzon, CEO, BenchSci. “We’re using breakthrough machine learning technology to shape the future of how life science companies conduct research, from identifying targets, to planning experiments, to determining clinical trial risks.  The confidence demonstrated by global pharmaceutical companies who are early adopters of our new solutions was enough to convince Inovia Capital to fund another round and prompt TCV to back our meteoric hypergrowth.”

In previous funding rounds, BenchSci raised $60 million (US $47 million) from tier one investors including F-Prime, Gradient Ventures (Google’s AI fund), and Inovia Capital. In 2021, BenchSci doubled its team and industry user base and is poised to double again in 2022.

“We strongly believe that the preclinical R&D market remains largely untapped and that BenchSci can become a category-defining leader to bring life-saving drugs to market faster,” says Dennis Kavelman, Partner at Inovia. “Doubling down on a company that we believe in is part of our commitment to being a long-term partner to build global sustainable tech companies.”

BenchSci’s proprietary machine learning models—trained to understand experiments like a Ph.D. scientist—extract critical insights from published scientific data sources and pharmaceutical organizations’ internal databases. The models understand the biomedical significance of extracted data and establish relationships between biological entities. This technology is the foundation of all of BenchSci’s applications, which surface the appropriate information and insights to assist scientists at top global pharmaceutical companies in various stages of R&D. 

“The preclinical research market is in dire need of software to drive efficiencies in the discovery through development process,” says Matt Brennan, General Partner at TCV.  “BenchSci is well-positioned to be the category-defining technology platform for the industry, and we look forward to working with Liran and his team to transform this industry.”

Founded in 2015, BenchSci has rapidly grown its customer base since launching commercially in 2017.  As a Deloitte Tech Fast 50 company, it is one of the fastest-growing companies in the country.

For more BenchSci updates, visit our news page

About TCV 

Founded in 1995, TCV was established with a clear vision: to capture opportunities in the technology market through a specialized and consistent focus on investing in high-growth companies. Since inception, the firm has built a track record of successfully backing public and private businesses that have developed into dominant industry players across internet, software, FinTech, and enterprise IT. TCV has invested over $16 billion to date and has helped guide CEOs through more than 145 IPOs and strategic acquisitions. TCV has invested in cutting edge technology companies including Airbnb, Believe, Brex, Dream Sports, FarEye, Mollie, Nubank, Razorpay, RELEX Solutions, Revolut, RMS, Sportradar, Spotify, Trade Republic, The Pracuj Group, and Zepz. TCV has successfully executed over 350 investments of varying structures, including mid-stage, late stage, and public company investments, and has offices in Menlo Park, New York, and London. For more information about TCV, including a complete list of TCV investments, visit

About BenchSci

BenchSci’s vision is to bring novel medicine to patients 50% faster by 2025. We’re achieving it by empowering scientists with the world’s most advanced biomedical artificial intelligence. Backed by top-tier investors including Inovia Capital, TCV, F-Prime, Gradient Ventures (Google’s AI fund), and Golden Ventures, our platform accelerates science at 16 top-20 pharmaceutical companies and over 4,500 leading research centers worldwide. We’re a remote-first Deloitte Tech Fast 50 and CIX Top 10 Growth company, certified Great Place to Work®, and top-ranked company on Glassdoor. Learn more at

Media Contacts:

Marie Cook, BenchSci

Katja Gagen, TCV