The mental healthcare industry in the U.S. is at an inflection point: Patients can’t easily find help while therapists are overworked, underpaid, and frustrated with traditional employment options. Therapists are increasingly dissatisfied with the groups they are employed by and 80% are looking for a new way to engage with patients.
Launching one’s own practice is hard. Self-employed therapists must navigate complex payer relationships to offer in-network coverage, tap channel and referral networks to build their book of patients, manage burdensome administrative work, and cultivate a network of peers for collaboration and support. The industry’s antiquated practices are directly impacting patient outcomes and clinical quality.
Grow’s B2B2C platform enables therapists to launch their own independent practice and in doing so, enables therapists to expand access and better serve patients.
With Grow’s complete ‘practice-in-a-box’ solution, self-employed therapists can offer affordable insurance-covered care to patients without having to worry about patient acquisition, overhead, or other administrative burdens that often fall on independent private operators (e.g. EHR, scheduling, invoicing, payment collection, note taking tools). Grow also provides a community for therapists to engage and connect with other providers in the field. 70%+ of providers use the Grow Community weekly and many cite this feature as a reason for their success on Grow.
For patients, Grow offers a convenient path to find the right in-network behavioral health provider, book time instantly on their calendar, and access confidential secure care either virtually or in-person.
Team on a mission.
The idea for Grow came from CEO and Co-Founder Jake Cooper’s experience with the difficulties of finding in-network behavioral care. After many dead-ends, Jake decided to pay out-of-pocket for a provider not covered by his insurance. While he had the resources to tap a provider out-of-network, Jake knew most Americans did not.
Jake partnered with co-founders Alan Ni and Manoj Kanagaraj, as well as a broader team with deep experience across technology, healthcare, and payments, to build a mission driven company which empowers therapists to launch their own independent practices that are: 1) covered by the largest number of insurance providers in the industry, 2) easily discoverable by patients, and 3) scalable due to full-stack supporting infrastructure.
Our partnership with Grow.
We’re thrilled to announce that TCV has led Grow’s Series B. In this round, Grow has raised $75M in equity and debt capital from TCV and other leading investors including Signalfire and Transformation Capital.
At TCV, we look to partner with founders who are building category-defining, generational companies and we’re incredibly excited to partner with Jake, Alan, Manoj, and the rest of the Grow team on their mission to create the largest and most accessible behavioral health platform in the country.
We’re still in the early innings of AI adoption, yet we’ve already seen it transform industries. Companies like Netflix, Spotify, and Uber have scaled internal teams from a handful of data scientists and machine learning (ML) engineers to hundreds. These teams, and the models they built to inform business and product decision-making, have shaped how consumers watch television, listen to music, and hail rides.
As AI use cases abound, ML teams face growing challenges around how to build, deploy, and maintain their models. Practitioners demand the flexibility to optimize each component of a model and, like software development, use specific tools to address the various phases of the model development lifecycle. In an attempt to bridge the development gap in ML, a new framework called MLOps has emerged. MLOps is derived from core DevOps principles and represents one of the fastest growing markets in technology today.
To date, MLOps has largely centered on data preparation, model training, and model deployment; however, building and deploying models is only the beginning of the journey. What happens once a model is running in production? The reality is most companies still lack the necessary tools to scalably monitor and understand their live models. Moreover, as these models become more complex, troubleshooting issues gets harder and both upstream and downstream problems compound.
In order for AI to achieve long-term sustainability, companies must improve model transparency, understanding, and performance. Enter Arize, a ML observability platform built by practitioners to help unpack the proverbial AI black box and optimize the performance of models in production.
Shaping the future of AI infrastructure
As the various components of the model lifecycle standardize, many companies have started to orient away from expensive in-house builds and less flexible integrated platforms. Instead, practitioners are opting for best-of-breed MLOps solutions from focused vendors like Arize to gain additional control over their modeling workflow.
Arize sets itself apart as one of the few platforms that sits at the center of production ML. Within MLOps, there has been a flood of investment in tools addressing data preparation all the way through to the model deployment stage, but few tackle the reality that all live models face over time: degradation. Without real-time monitoring and observability, ML teams spend countless hours pouring over anomalies and trying to understand problems in the data, software, and / or model itself. Arize’s observability platform seamlessly plugs into any MLOps stack and provides a scalable solution to monitor the performance of models, explain what the models are trying to do, and diagnose data and drift issues without going back to square one.
In speaking to Arize’s customers, which include many of the world’s most sophisticated ML teams, it’s clear observability is seen as a core pillar of AI infrastructure and represents a natural progression in how they think about model lifecycle management. There’s a reason adjacent observability solutions like Datadog and Monte Carlo exist in other areas of IT, and we believe ML will be no different.
Built by practitioners
Arize’s founders, Jason Lopatecki and Aparna Dhinakaran, first met at TubeMogul, where Jason was a founder who helped build out the company’s ML team and Aparna was a data scientist. Jason would eventually guide TubeMogul through a successful IPO and sale to Adobe while Aparna went to work for Uber as part of its famed Michelangelo team.
Jason and Aparna stand out in a MLOps space where many founders hail from academia. Both draw from deep practitioner roots and have experienced firsthand the heartache of spending months building and training models, deploying them to production, and having no insight into how the models actually performed once deployed. Independently, they came to the conclusion that something was fundamentally missing in the MLOps toolchain. Together, they are now focused on bringing transparency, understanding, and performance to production ML through Arize’s dedicated observability platform.
Our partnership with Arize
We’re thrilled to announce that TCV has led Arize’s $38M Series B alongside our friends at Battery Ventures, Foundation Capital, and Swift Ventures. At TCV, we gravitate towards founders that are culture and product obsessed. Jason and Aparna blend multi-stage company-building experience with firsthand knowledge of a real customer pain point. We’re incredibly excited to partner with the Arize team on their mission to make AI work and work for the people. If you are interested in joining Arize for the journey ahead, please visit their website to learn more about current career opportunities.
Digitization of healthcare provider business processes and workflows is one of our healthcare team’s key investment themes. Our focus on this theme is a derivative of several industry dynamics affecting hospitals and physician practices, including reimbursement headwinds that are pressuring already slim operating profit margins, workforce shortages and high employee turnover, and a reliance on manual, labor-intensive, and / or paper-based methods to facilitate key business processes, among others. Put simply, across front, middle, and back office applications, we believe healthcare providers will increasingly adopt automation software to drive operational and financial efficiencies, increase workforce productivity, improve employee retention, reduce burnout of clinical personnel, and, perhaps most importantly, improve the patient experience.
In baseball terms, we believe the healthcare industry is in the “early innings” with regard to software adoption. While provider organizations have spent the last 10-15 years adopting electronic medical records (EMRs), they continue to lag other verticals in terms of software adoption for managing and / or automating various business processes. As one example, healthcare providers have only recently begun implementing customer relationship management (CRM) software platforms, while most other industries have had CRM systems for decades. To this juncture, automation software (often termed “robotic process automation” or “RPA”) adoption in healthcare has largely focused on back office applications – revenue cycle, specifically. However, we believe automation of front-office workflows through technology – healthcare’s “digital front door” – will have the most profound impact on the patient experience, while also driving significant operational and financial value for providers.
It is against this backdrop that we are delighted to lead Syllable’s $40M Series C financing in partnership with our friends at Oak HC/FT, Section 32, and Verily Life Sciences. Our investment in Syllable is intended to help Syllable expand its artificial intelligence and machine-learning (AI/ML) enabled software platform into adjacent applications and use cases, penetrate new healthcare customer segments (e.g., payor, pharmacy, etc.), rapidly scale headcount across all functions, and forward invest in future growth initiatives.
There has been a lot of “buzz” recently regarding the healthcare industry’s “digital front door,” which we define as simply the technology-enabled mediums via which patients engage with the healthcare system. This is largely a function of the growing consumerization of healthcare and corresponding emphasis on improving the patient experience, and numerous technologies have emerged to help facilitate digital interactions between patients and providers. Having said that, our research – and data from Syllable’s customers – indicates that the dominant modality for patient engagement with providers remains a telephone call; in our view, this is a derivative of the uniqueness of an individual patient’s circumstances and needs, in addition to the complexity of the healthcare system and its historically limited or non-existant digital channels. As a result, we believe the technology platforms best-positioned to automate front office workflows must offer solutions that address both voice and digital mediums.
Enter Syllable and its CEO, Kobus Jooste. Kobus founded Syllable in 2017 with an initial vision to build a software platform capable of removing high-friction barriers between healthcare providers and their patients. Prior to founding Syllable, Kobus spent several years in engineering leadership roles at Google, the most relevant of which was his leadership of the engineering team that developed and launched Google Assistant. Given Kobus’ background in conversational AI and natural language understanding (NLU), we believe that he is well-positioned to build a platform capable of automating both voice and digital patient-provider interactions. More specifically, Syllable’s technology platform leverages AI and NLU to automate inbound patient interactions with providers via phone, web, chatbot, and SMS text. As 95%+ of all patient interactions with providers presently take place via phone call, healthcare providers invest heavily in call center operations – anecdotally, some of Syllable’s customers field 15M+ patient phone calls per year, and invest hundreds of millions of dollars in their own call center personnel and operations. At the same time, providers are also investing significantly in digital applications to facilitate more efficient patient engagement.
Despite this level of investment, the healthcare industry continues to lag others in terms of consumer (i.e., patient) experience. As one datapoint, healthcare’s average net promoter score (NPS) is approximately 27; an NPS of 50 to 70 is generally considered “good.” As another, healthcare providers have call abandonment rates close to approximately 30% (per data from Syllable’s customers) – one of many reasons underpinning a poor patient experience. For providers, a poor patient experience negatively impacts their revenue from multiple vantages; for example, calls abandoned may represent lost revenue opportunities, and a poor experience with a provider reduces the probability of a repeat visit. Properly and efficiently engaging patients is incredibly challenging, as any digital mechanism for managing interactions needs to be highly approachable for patients, must incorporate healthcare-specific contextualization in terms of the intent of the interaction, requires immense scalability (e.g., large systems have 15M+ inbound phone calls annually), and, to reiterate, must facilitate engagement across both digital and voice channels.
That’s precisely the problem that Syllable is out to solve. Syllable’s technology platform leverages conversational AI and NLU technology in tandem with the company’s purpose-built digital applications to automate inbound patient interactions with healthcare provider organizations. Across the company’s current customer base and use cases, Syllable’s platform is capable of automating the majority of inbound patient inquiries, and those inquiries it cannot drive to a conclusion without human intervention are routed to the customer’s call center personnel for further triage. Common use cases include routing calls to the correct endpoint, appointment scheduling, and referral and medication management, among several others. What’s more – Syllable’s ML technology trains its AI on those interactions it cannot automate such that the company’s automation percentage improves with incremental volume and customer utilization. Syllable’s data suggests that its platform drives hard ROI for customers across multiple dimensions, including a significant reduction in call abandonment rates (to zero with Syllable’s platform) and wait times, a 2x+ or greater increase in first call resolution rates, and higher appointment scheduling conversion rates, among others – all of which result in an improved experience for patients.
Syllable’s compelling value proposition, coupled with its reputation for relentless innovation and top-tier customer service, contributed to engendering customer delight, and the company boasts an NPS of 80+. Its customers include numerous healthcare provider organizations, including Parkview Healthcare, Shannon Healthcare, New York Presbyterian, Weill Cornell Ambulatory Care Network, Houston Methodist, and Mass General-Brigham, among others – a particularly impressive roster given the company only began marketing its platform in October 2021. In 2021, Syllable interacted with 39.7M Americans in text and voice about primary care, specialty referrals, vaccinations, and general practice information. Based on Syllable’s sales momentum, the company will more than double its revenue in 2022, particularly as Syllable scales product and technology resources and continues to add to its go-to-market organization.
CEO Kobus has assembled an impressive team of advisors and experts to advise Syllable on the healthcare industry’s needs and complexities, in addition to AI and ML technology. With this in mind, we are excited to have TCV Venture Partner Anita Pramoda support Syllable as the company takes-on new challenges in the healthcare industry.
“Syllables compresses the delay between needing and accessing care,” says Anita. “With Syllable, healthcare providers can now bring reliability, repeatability, and ubiquity to access – foundational tenets of good health. I’m honored to partner with Kobus and the entire Syllable team as they scale their platform and offer better care for all patients.”
Growth metrics and accolades aside, what perhaps impresses us most about the Syllable team is its unwavering commitment to approaching the healthcare industry with humility and respect. For a brief anecdote on this front, please refer to this segment with Joe and Syllable’s CMO, Adam Silverman, on a recent episode of the company’s podcast.
“Syllable is at a crucial point in its growth trajectory. As one of the most transformative platforms for health systems, our vision is clear. We want to help as many patients navigate hospital and primary care, while lowering the cost of access to care and the burden on front office staff and clinical staff,” says Kobus.
Syllable was also recognized as a most promising startup in healthcare for 2022 by CB Insights, picked as a leader in the private market from a pool of 7,000 companies – chosen based on R&D activity, proprietary Mosaic scores, market potential, business relationships, investor profile, competitive landscape, team strength, and technology novelty.
We are off to the races in our partnership with the Syllable team – including newly-appointed COO Catherline Krna, who joins Syllable from the Chief Administrative Office of Ambulatory Care and Service Lines at Stanford Health Care. We are incredibly excited to help build what we believe is a category-defining, generational software company that engenders patient delight while driving operational and financial efficiencies for healthcare providers.
TCV’s healthcare team has long been pursuing a thesis around the utilization of healthcare data, particularly for applications in the life sciences industry. Specifically, we believe that companies with proprietary technology that enables them to aggregate, curate, and contextualize healthcare data have a tremendous opportunity to layer on software applications and help address a myriad of downstream use cases for their customers. Our Series C investment in BenchSci, completed in partnership with our friends at iNovia Capital and F-Prime Capital, provides an illustration of this thesis in our portfolio – one of many, we hope, over the next few years. The Series C funding is intended to help BenchSci expand the company’s artificial intelligence and machine learning-enabled software platform into additional applications, rapidly scale headcount, and forward invest in future growth initiatives.
BenchSci was founded in 2015 by CEO Liran Belenzon, Chief Science Officer Tom Leung, Chief Data Officer Elvis Wianda, and co-founder David Chen who met one another through the University of Toronto’s Creative Destruction Lab. The company’s technology platform endeavors to increase productivity and efficiency in the preclinical research process for pharmaceutical and biopharmaceutical organizations. The life sciences industry spends an extraordinary amount on preclinical research as these efforts help develop a pharmaceutical or biopharmaceutical company’s core intellectual property. We estimate global preclinical expenditures at ~$80B annually, or ~40% of total research and development investment for life sciences firms, and scientists at pharmaceutical and biopharmaceutical companies perform tens of thousands of preclinical experiments per year.
Despite this level of investment, preclinical research has long been plagued by inefficiencies. BenchSci’s customers estimate that approximately 80% or more of preclinical experiments performed yield no value to their overall research efforts; relatedly, it is extremely challenging to identify potentially wasteful or redundant experiments a priori. This process continues to be one of trial and error – more “art than science” – and limited technology tools exist to help scientists become more productive. Moreover, the data captured in the context of these efforts exist in disparate, siloed systems, thereby inhibiting information sharing and collaboration even within a life sciences company. Even when successful, a preclinical research process takes between six to seven years on average, thereby delaying time-to-market for life-saving medicines.
The problem described above is the one CEO Liran and his team are determined to solve via technology. The company’s mission is to deliver technology that helps scientists bring novel medicines to market 50% faster by 2025. To do so, BenchSci has built a comprehensive preclinical experiment-focused knowledge graph, encompassing data on over 40 million experiments. Consistent with our framework outlined above, the company has built software and computer vision technology that automates the stitching together and curation of experimental, bioinformatic, and other data from numerous, disparate sources, including its customers’ own internal data. Further, the company’s team of PhD scientists works alongside BenchSci’s product and technology teams to contextualize BenchSci’s 100+ machine learning models and algorithms such that its knowledge graph and results make “scientific sense” to scientist end-users as they leverage the company’s technology platform.
BenchSci’s flagship application was launched in 2017, and leverages artificial intelligence to help scientists select the optimal antibodies and/or reagents to use in their experiments based on experiments previously performed that are relevant to the study in question. This saves scientists significant time and resources – customers indicated to us that they have saved tens of millions in hard costs alone by eliminating redundant/wasteful reagent purchases, not to mention the time savings (several weeks to months per project) and other efficiencies they’ve realized. The company is not stopping there, and we are particularly excited about what BenchSci is going to do next with its breakthrough technology that will shape the future of preclinical research, although we will leave it to Liran and his team to share more in the coming months.
BenchSci’s compelling value proposition, coupled with its reputation for relentless innovation and superb customer service and support, has engendered customer delight, and the company boasts a net promoter score of 80+. Its customers include 16 of the top 20 pharmaceutical companies (by revenue), in addition to over 4,500 leading research centers globally, and its platform is being used regularly by 50,000+ scientists. CEO Liran has scaled the organization to meet latent demand – BenchSci has grown its employee base more than 8x in the past three years, and expects to reach 400+ employees by the end of 2022. The company has been recognized as a Deloitte Tech Fast 50 company and a CIX Top 10 Growth company.
CEO Liran has also lined-up an impressive team of advisors and experts to advise BenchSci on life sciences research and development, organizational culture, and artificial intelligence and machine learning technology, including TCV Venture Partner Jessica Neal (former Chief Talent Officer at TCV portfolio company Netflix).
“BenchSci plays an important role in curating and contextualizing healthcare data to increase productivity in the preclinical research process,” says Jessica, “and I look forward to supporting Liran and his team as they continue to scale.”
Growth metrics and accolades aside, what also impressed us about BenchSci is Liran’s unwavering focus on fostering BenchSci’s culture. Liran believes the company’s distinguished culture is instrumental to its success, and he endeavors to build an inspiring, inclusive, and equitable work environment where employees are set up to thrive and have a meaningful career. Starting with Liran, it was clear during our diligence that BenchSci’s employees pursue continuous improvement and a high-degree of transparency and candor. The results speak for themselves – BenchSci has been named a certified Great Place to Work® and is a top-ranked organization on Glassdoor. We are excited to add Jessica Neal to BenchSci’s advisory board to help Liran continue to develop and grow the company’s culture as BenchSci scales through its next major inflection points.
“Our recent Series C raise enables us to build and deliver a next generation AI solution for global pharmaceutical companies that will enable scientists to exponentially improve their preclinical R&D work,” says BenchSci CEO Liran Belenzon. “We are a mission-driven organization intent on achieving success beyond success, and I’m excited that TCV recognizes our market-leading potential and has chosen to back our meteoric hypergrowth.”
We are off to the races in our partnership with Liran and the BenchSci team, and are incredibly excited to help build a category-defining, generational software company that drives productivity and efficiency in the preclinical research process, thereby bringing novel, life-saving medicines to patients faster.
Software development is a $2 trillion industry – yet today’s “software supply chains” have become increasingly challenging to govern and secure as agile development practices have evolved in the modern cloud era. Legit Security, a recent addition to TCV’s portfolio family, is on a mission to change that by providing end-to-end governance and security throughout the entirety of the software development lifecycle.
Software now plays an important role in nearly every business; it is one of the most critical assets empowering organizations to create efficiencies and competitive differentiation. Software development practices are constantly evolving to improve business agility and enable new digital business models, but as a result, software supply chains are also changing, have become highly complex, and are increasingly difficult to govern and secure. Too often, the code, pipelines, development infrastructure, and third party resources within the software development lifecycle (SDLC) are left insecure, exposing the organization to potential breaches and software supply-chain attacks.
The damage inflicted by software supply-chain attacks has gained publicity following events such as log4j and Solarwinds. However, these attacks were not isolated, and it’s estimated that software supply chain attacks are increasing at a rate of two to six times per year. As a result, the importance of bringing security and governance to the entirety of the software supply chain is becoming top of mind for businesses globally.
Introducing Legit Security: Security for software supply chain environments
Legit Security, an Israeli-based security company founded in August 2020, aims to address this acute pain point by providing a security platform that protects the pipelines, infrastructure, code, and people within software supply chains so that businesses can stay safe while releasing software quickly. The platform provides security and developer teams with a “single pane of glass” to secure the SDLC by scanning development pipelines for gaps and leaks, the SDLC infrastructure and systems within those pipelines, and the people and their security hygiene as they operate within it.
Legit Security’s platform aims to remove blind spots and automate governance and compliance for the software supply chain. The platform uses an automated discovery and analysis engine to identify vulnerabilities, measure and track the security posture of teams and development pipelines, and ensure compliance to regulatory and governance frameworks in real-time. By using Legit Security, security and development teams can manage risk more effectively and increase efficiency by focusing on what’s most important.
“Legit provides a single pane of glass to mitigate software development risk. We’re now able to inventory all our SDLC systems and security tools, view developer activity, and detect and remediate vulnerabilities across them fast. Legit’s security scoring also allows me to measure the security posture of different teams and show progress improving it.” – Bob Durfee, Head of DevSecOps at Takeda Pharmaceutical Company
Deep cyber security expertise
TCV is investing in Legit Security through its recently-announced Velocity Fund, which aims to invest in expansion-stage companies in its sectors of interest.
The founders and executive team of Legit Security have deep experience in cybersecurity. The founders all came from Checkmarx, a leading application security testing business, and had initially met in the Israeli military’s intelligence unit. As cybersecurity researchers and team leads for the renowned Israeli Defense Force’s Unit 8200, they gained real-world security experience with the offensive and defensive tactics specific to software delivery pipelines.
CEO & Co-Founder Roni Fuchs was formerly Senior Director and Head of Software Composition Analysis at Checkmarx, after his previous startup Lumobit was acquired by Checkmarx less than a year after its launch in 2018. Previously, Roni was a senior software engineer at Microsoft. Liav Caspi, CTO & Co-Founder of Legit Security, and Lior Barak, the company’s VP of R&D and Co-Founder, share similar backgrounds: all three overlapped at the Israeli military, Lumbobit, and Checkmarx. Chris Hoff, VP for Worldwide Sales was most recently Regional VP of Sales at Duo Security, having previously held sales roles at EMC, Kaspersky, Cognos, Watchfire/IBM, and CA Technologies. Derick Townsend, VP of Marketing, was most recently VP of Product Marketing at Ping Identity, with prior marketing leadership roles at UnboundID, DXC, ServiceMesh, CA Technologies, iTKO, and IBM.
Shifting left: The vast “DevSecOps” opportunity
So why are we so excited? Well, on top of the deeply relevant and honed skills that run through the company from its highest level, we believe that Legit Security is on to something big and important in the application security space. Over the past five years, as application development practices have evolved, the notion of “DevSecOps” (development, security, and operations) or “shifting left” has become increasingly popular.
“Shifting left” aims to make security more agile, repeatable, and automated, ultimately empowering DevOps teams to bring products to market faster. Existing application security solutions generally operate in isolation, resulting in silos throughout the pipeline. Further, blindspots can exist along development pipelines and SDLC systems and infrastructure, including GitHub / GitLab repos, which are not covered by traditional application security tools. In addition, the disparate nature of traditional AppSec tooling requires security teams to navigate across the numerous point solutions to try and stitch together insights into potential vulnerabilities, often leading to “alert fatigue.”
Legit Security bridges this gap by spanning the SDLC with automated discovery and analysis capabilities that include auto-detection of code repositories, build servers, artifact repositories, and deployed security products such as Snyk and Veracode along with their security coverage. When your SDLC changes, it’s automatically detected by Legit. The platform provides hundreds of best practice software supply chain security policies that can be enforced directly in the product, as well as a unique Legit Security Score to manage risk, track security posture, and monitor compliance to regulatory and governance frameworks in real-time.
This holistic, end-to-end insight enhances governance at various checkpoints, empowering enterprises to derive greater value from existing security tools. It’s no coincidence that customers frequently describe the Legit Security Platform as their “application security command center.”
Where are we now?
Legit Security has now emerged from its pre-launch phase, during which the company has been busy acquiring customers (from Fortune 500 companies to fast moving software-driven businesses), building a platform for demanding enterprise environments, and securing funding from top-tier investors,including TCV. The business has already grown significantly with new offices in the U.S. and Israel, and an expanded team, as well as connections with important partners and advisors.
I’ve known co-founders Liav and Lior for many years, since our time working for the Israeli Defense Forces. We gained invaluable experience there, but perhaps most important was learning that ‘anything is possible’ in cybersecurity with the right talent, focus, and resources.”
Roni Fuchs, CEO & Co-Founder, Legit Security
After military service, the founding team members worked in leading cyber security companies across Israel and recognized a growing gap between traditional AppSec tools and a new generation of rapidly evolving, modern software development environments. The gap was growing and traditional security tools and vendors were unable to catch up.
“Because of the adoption of agile development, cloud, and modern development pipelines, the approach needed to secure software releases has fundamentally changed. It’s no longer just about ‘the code’. Software is now assembled in multiple steps across a supply chain leveraging many trusted contributors, pulling artifacts from countless repositories, built, and assembled on underlying infrastructure that must be securely configured, and all the while providing speed, agility, and efficiency. These modern supply chain environments created a sprawling new attack surface – one that is increasingly exploited by over 2x-6x a year, depending upon the analyst, government agency, or vendor report you read.” – Roni Fuchs, CEO & Co-Founder, Legit Security
TCV team members Matt Brennan (TCV General Partner), Tim McAdam (TCV General Partner), Mark Smith (TCV Venture Partner), and Alex Gorgoni (Investor) are excited to partner with Legit Security, helping to guide the company through its next critical phase of growth. Our team has witnessed first-hand the enthusiastic response of customers as they learn about the unique positioning and scope of the Legit Security platform, and its ease of deployment.
This is a sector we expect to be active in over the coming months, too, and we look forward to being a part of it.