Growth Equity Enters the AI Debate

In March, the release of GPT-4 sent the VC ecosystem into a frenzy. Investors were all asking the same question: which new companies were going to make it big? Capital poured in. By one estimate, VCs invested almost five times as much into Generative AI startups in the first half of 2023 as they did during the same period last year (Source: Pitchbook). Several Generative AI startups took advantage of the fundraising rush, raising hundreds of millions of dollars without a single cent of revenue. 

Now, it is time for us to have a say. TCV seeks to invest in companies which have proven product-market-fit, a history of execution, and sustained revenues. Over the years, we have made many AI investments, but we have not yet made any native Generative AI investments. That time is coming. So we wanted to offer our thoughts on the risks and opportunities in the AI space as we see them. 

What are we talking about, in its simplest form

Source: TCV

Recent AI tools are so impressive that it is easy to get carried away with the “what ifs.” We are asking ourselves: to what extent are we buying the hype? And to what extent are we seeing a paradigm shift in technology? So far, we see the following strengths, weaknesses and opportunities: 

Just don’t believe the hype 

LLMs are enormously powerful, but they aren’t a silver bullet (yet) 

Source: TCV

To focus the discussion further, in a recent internal exercise we assessed which business characteristics were a) weaknesses and b) strengths in the era of AI. The full table is shown below, but a few themes stand out: 

Weakness 1: Publicly available data. Some companies draw on large bodies of freely available text and images. They aggregate it, curate it, and then deliver content to customers. This business model directly competes with many Generative AI models, which scrape the internet to train themselves. The problem is that Generative AI models do it better. 

True, these companies will often say that, on top of the publicly available data, they are creating their own content. An AI chatbot would, though, make exactly the same argument. 

Weakness 2: Routine cognitive tasks. In analyzing the labor market, economists classify jobs as being either routine or non-routine, and cognitive or non-cognitive. Routine cognitive jobs account for about a quarter of total jobs across the United States. These are jobs which require some element of brainpower, but where there is little creativity, accuracy does not have to be perfect, and the job on day 1 is similar to the job on day 2. 

Some businesses are highly reliant on routine cognitive tasks. For example, personalization, translation, and localization services can be automated by AI at near-zero cost. So too can repetitive data entry and processing tasks. The same goes for content creation, if the product is something that merely has to be “good enough” rather than genuinely compelling. 

Weakness 3: Old-school AI. There are numerous examples of AI systems being deployed at scale. Just consider the autocomplete function when searching on Google. Some building-management systems use AI to help with heating and cooling. Some worry that the providers of these services will soon be outcompeted by the vastly more capable tools associated with Generative AI. 

Value-at-risk framework

Characteristics that might cause a business to be more vulnerable to AI disruption/disintermediation

Source: TCV

Strength 1: Trust. A growing share of services in the modern economy could be described as YMYL – or, “your money, your life.” These are things where you cannot afford for things to go wrong, such as healthcare, education, and insurance.

In these industries, the barriers to adoption of AI could be high. Managers will be nervous to trust something that is almost human, but not quite human. In addition, these industries are often highly regulated. As a range of evidence shows, technological progress in highly regulated industries tends to be slow. If you’re still filling out paper forms when you go to the doctor, how likely is the practice to adopt Generative AI any time soon?

Strength 2: Network effects. Companies that rely heavily on understanding customer data have a virtuous compounding moat. These companies can focus on using AI to augment human capability through their own channels. Proprietary data and processes can be used to build better algorithms or models. These companies will drive AI use cases, rather than be displaced by the technology.

Strength 3: Human-to-human contact. If customers have an emotional connection to a brand, this often requires emotion, high-touch sales, or some other form of personal interaction. As of today, AI cannot fully replicate human connection – and may never be able to do so. The same is true where content is predominantly about shared experiences and social capital.

More trivially, AI is unlikely to disintermediate companies that rely on physical services. We believe tradespeople like electricians and stonemasons are well-positioned to weather whatever comes next.

Conversely, sustainable moats framework 

Source: TCV

Given these risks and opportunities, what should growth companies do today? This is a question that companies pose to us on a near-daily basis. First, the company should consider whether AI can provide a real advantage. Second, the company should explore the best path to a production use case. This often means combating human capital limitations, addressing data privacy concerns, or having some ability to accurately evaluate model performance.

Where we hear problems arise in the LLM toolchain

Source: Arize, TCV

Here’s how to think about incorporating AI. There are, we believe, many potential barriers to adoption, as the table below outlines. 

Key limitations

LLMs and Generative AI have shown impressive potential, but there are limitations that may hinder widespread adoption

Source: TCV

In the short term, companies can draw on publicly available LLMs – large language models – like GPT-4 to start thinking about proof of concept. That is all well and good, but the proper use of AI goes far beyond simply using the occasional chatbot. Instead, it involves the full-scale reorganization of firms, as well as their in-house data. What does that mean in practice? At a lower level, it means leveraging a publicly available model with context from the company’s own data and products. At a higher level, it means training or fine-tuning a foundation model, where the company maintains full control and ensures data privacy.

Selecting the right approach to LLMs 

Source: Arize, TCV

Operationalizing AI efficiencies is also top of mind for our portfolio companies. It is not lost on us that the best performing companies will be those that continuously think about their cost structures and how to leverage new technologies to improve margins. Some of our portfolio companies are creating “synthetic P&Ls” to understand what their optimal cost structures could look like by leveraging AI, while other bestin- class companies are employing AI “SWAT teams” to ascertain how they might use AI internally and in their products.

Future P&Ls? 

Source: TCV

We are still at an early stage. The world has quickly moved from traditional AI systems to Generative AI. Things are bound to continue to change, and over time our thinking about the risks and opportunities of AI will continue to evolve. We look forward to receiving your comments.


The views and opinions expressed herein are those of the author and do not necessarily reflect those of TCMI, Inc. or its affiliates (“TCV”). This blog post is strictly for informational purposes only and is 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. TCV has not verified the accuracy of any of the data or statements by the author and disclaims any responsibility therefor. Any TCV portfolio company identified in the blog post is 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 blog post, please see “Informational Purposes Only” in the Terms of Use for TCV’s website, available at

Modernizing hourly work: Our investment in Instawork

The pandemic has shown businesses the benefits of flexible staffing from the ability to ramp up or down labor during seasonal periods to reducing fixed costs and increasing flexibility during unforeseen macro events. Coming out of the pandemic, the US has three million fewer Americans participating in the labor force compared to February 2020, prompting the need for tech-forward solutions to better match the limited supply of workers with the growing demand.1 

The staffing market is giant, fragmented (no company >2% mkt share), and underpenetrated by technology, with most players employing people-heavy models. Legacy temporary staffing agencies are heavily people-operated. Temp staffing agencies maintain large customer service and account management teams, often manually calling or emailing/texting workers to inform them of shift availability and, on the employer side, exchanging spreadsheets or calls/emails/texts about scheduling, payment and more.

This disjointed and often analog process results in mismatched expectations, frustrating experiences, and suboptimal matching of labor supply and demand, worsened by high turnover and frequency of hiring. An employer running a catering business or warehouse operation,  often faces 100%+ full time employee turnover on an annual basis. 

Instawork offers a mobile-first job marketplace and workforce management platform for skilled temporary workers, bringing flexible work to hourly workers at scale.

Instawork makes it easy for employers to list shifts and for workers to discover and book them, along with facilitating payment and creating trust with transparent/public performance management for both sides.

Pros have fast access to quality jobs, a transparent booking and payment experience, the ability to build their skills through a two-sided review system, and the capability to receive recognition and rewards for their performance. Instawork offers flexibility that hasn’t previously been offered to Pros; they can set their own hours and can change their work preferences each day, week or month as well as earn more for urgent requests and peak times.

The value proposition to partners is reliability, quality, and convenience. The underlying data model plays a critical role in properly matching skilled workers to available shifts and the performance of both the partner and worker is tracked for future matching success. 

The flywheel is working: fill rates (% of positions listed that are filled) have increased over time and no show rates have decreased over time with scale, demonstrating how Instawork’s data-fueled matching system has funneled increasingly reliable and quality workers to employers, resulting in high satisfaction from employers and workers. To date more than4M Pros have joined the Instawork platform and partners are increasingly pulling the company into new geos across the US and Canada.

Our partnership with Instawork

We’re thrilled to announce that TCV has led Instawork’s Series D. In this round, Instawork has raised $60M of capital from TCV and other investors including Benchmark, Spark, Greylock, Craft, 9Yards and more.

We have a deep belief at TCV that strong and fitting company cultures result in great experiences for customers. While learning about Instawork, we heard that the team had a saying “Inches off at launch means miles off in orbit.” It’s exactly this detail orientation and product obsession that we think can give rise to a novel marketplace platform for hourly work. We’re incredibly excited to partner with Sumir and the rest of the Instawork team on their mission to shape the future of work.


Improving the patient experience with AI/ML software: Our investment in Syllable

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.


The views and opinions expressed are those of the author and do not necessarily reflect those of TCMI, Inc. or its affiliates (“TCV”). TCV has not verified the accuracy of any of the data or statements by the author and disclaims any responsibility therefor. This blog post is 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 above 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

TCV invests in Evisort to deliver scalable, AI-powered contract management

Contracts are at the heart of business, enshrining a company’s rights and obligations across areas ranging from sales transactions and supplier relationships to employment agreements and beyond. Resulting from this centrality, rising contract volumes and legal complexity have made contract management unmanageable without leveraging technology.

Evisort delivers end-to-end contract intelligence software that turns contracts into data. Customers use a simple, intuitive interface to extract critical context from contracts, integrate that data into other enterprise systems, and automate a wide range of legal and operational workflows – themselves codified in contract data. Evisort’s platform is powered by award-winning AI that is purpose-built for contracts and trained on over 10 million documents, thereby driving a differentiated customer experience and rapid, tangible ROI.

We are thrilled to announce TCV’s Series C investment in Evisort. We believe that contracts have been both an under-managed source of risk and under-explored source of value for companies, and that Evisort’s AI-powered Contract Intelligence Platform solves increasingly important pain points for businesses of all sizes, ranging from the Fortune 500 to mid-sized companies alike.

Evisort was founded in 2016 by lawyers and technologists who saw the need for automation in contract management.  The platform started as an intelligent analytics engine that extracts clauses and metadata to index contracts and their contents, making them easily searchable and manageable without manual data entry. Evisort’s AI further contextualizes the contract, indicating what type of contract it is, identifying counter-parties, flagging auto-renewal dates, and more.

More recently, Evisort has been adding workflow capabilities – relevant for coordinating contracting processes and operational workflows across the business. Evisort’s end-to-end approach ensures that all contract data is located in one repository, minimizing security risks, reducing the number of required integrations, and allowing the system to apply learnings from previous contracts to new ones.

More than any other contract management software business we’ve evaluated, Evisort’s AI platform supports a wider range of teams, industries, and use cases. Sales teams use Evisort to drive sales and renewals by reducing contracting friction and speeding time to agreement and revenue recognition. Legal departments use Evisort to drive compliance, quickly find and report on critical information, and act as a single source of truth. Procurement and sourcing organizations rely on Evisort to accelerate purchases, negotiate stronger agreements, and manage supplier risks more effectively. In all cases, Evisort drives efficiency by reducing reliance on manual legal review – a major bottleneck in many contracting processes.

Transforming the future of contract management

Evisort’s Contract Intelligence Platform has three main capabilities:

AI-Powered Contract Analytics and Insights: Evisort extracts data from contracts, produces critical insights, and reports on those insights in an easy-to-use dashboard, so that users can focus on higher value tasks. This contract intelligence is then used to generate workflows across the organization. Evisort is focused on delivering the intelligence layer between core operating systems such as customer relationship management and enterprise resource planning platforms.

Intelligent Contract Lifecycle Management: Evisort provides contract request intake, contract drafting, approvals, version control, and repository (storage, search, reporting) features. Evisort’s platform creates a source of truth so teams can centralize knowledge, collaborate easily, and simplify contract administration.

Central Contract Repository and Integrations: Evisort’s no-code platform lets legal, sales, and procurement teams self-serve, taking the burden off of IT teams and providing immediate configurability. Evisort easily integrates into existing systems to minimize the need for data migration and accelerates deployment because employees can work from the systems they already use.

Why now: A big market waiting for the right end-to-end product

At TCV, we have invested extensively behind the digitization of the legal industry – having backed innovative legal technology industry leaders such as Clio, LegalZoom, and Avvo. As part of our work in this space, we have been closely following the evolution of the CLM market for nearly a decade. In that time, customers consistently indicated a desire to manage both new and existing contracts in the same place – in other words, a true end-to-end platform. Over the last several years, our conversations in the space increasingly indicated that Evisort’s founders Jerry, Jake, and Amine had built exactly that and Evisort’s platform was seeing accelerating adoption in a largely greenfield market.

Evisort customers – which include our portfolio companies such as Netflix – typically start with analytics use cases to understand existing contracts, and then add pre-signature workflow to more efficiently generate new contracts. From there, thanks in part to Evisort’s ease of use, usage often quickly expands to additional teams and stakeholders within their organization. For customers, the results are industry-leading time-to-value, implementation speeds, self-service analytics, and flexibility to apply contract-based insights to a wide range of business functions. For Evisort, a cohesive and forward-thinking strategy appears to have translated into an innovative and fast growing company in an exciting market.

Looking Forward

As we look to the future, we are incredibly excited about the tailwinds strengthening Evisort’s value proposition for its customers. Businesses of all sizes have more contracts and a greater need to manage them than ever before. The compliance and regulatory environment also continues to evolve, requiring businesses to maintain constant visibility into their contract corpus. And companies are increasingly leveraging the data embedded in contracts to drive business processes across sales, procurement, operations, and finance.

Given that robust backdrop, we are incredibly excited to work with Jerry, Jake, Amine and the rest of the Evisort team to maximize the opportunity for AI applications in contract management.


TCV Welcomes Edie Ashton as Chief Information Officer

Over the past 26 years, we have grown our portfolio companies and our own team to a point where TCV is operating across three offices in the U.S. and Europe. Due to the scale and global reach of our organization, we are excited to expand TCV’s executive talent to take us to the next level.

As such, we are thrilled to announce that Edie Ashton is joining the firm as Chief Information Officer (CIO). Edie was previously at The Carlyle Group, where she spent nine years, most recently serving as segment CIO for Global Private Equity. Adding Edie to our leadership team is a critical piece of our growth trajectory and demonstrates our ongoing commitment to deploy modern technology in support of our data-centric culture.

Edie comes to TCV with deep experience in both financial services and data strategy. As CIO, she will help advance growth by focusing on talent excellence, agility, and innovation in areas such as applied AI and distributed infrastructure—bringing a deeper alignment of IT and TCV’s core business as we pursue seamless global collaboration and acceleration of our investment platform.

Edie started her career at the Capital Group and Jefferies & Company, before enjoying a decade-long run in the telecom industry, implementing data warehouses and analytics platforms at global brands such as Nextel, Sprint, and RCN. At Carlyle, Edie proved herself a versatile business-oriented technologist who introduced the first data governance program and established a diversity and inclusion plan for the IT division.

“Edie is joining TCV at the right time,” says Nathan Sanders, General Partner and Chief Operating Officer at TCV. “We are experiencing significant growth and expansion of our team globally and have seen the benefits of leveraging sophisticated IT technology across our portfolio and TCV. Edie is a proven IT leader and tech visionary, focused on results that advance the whole organization. We are thrilled to welcome her to the TCV family.”