Part III: Business model invention in the AI era
Copilots, agents, and AI-enabled services are three new models delivering the benefits of artificial intelligence to vertical industries.
Brian Feinstein, Caty Rea, Kent Bennett, Byron Deeter, Sameer Dholakia, Mike Droesch, Maha Malik, Sam Bondy, Alex Yuditski & Aia Sarycheva
Published on Dec 5, 2024
Much like cloud computing transformed vertical industries over the past two decades, the human-like capabilities of LLMs — processing text, images, videos, voice, and code — are making it possible for Vertical AI to achieve what was previously unimaginable for sectors of the economy that only benefitted marginally from previous waves of software innovation. Vertical AI companies aren’t just streamlining workflows; they’re taking on vast, high-cost, language-heavy tasks that dominate industries like legal, healthcare, and professional services — sectors representing a 10x larger TAM than the software market itself.
The scale of opportunity is unmatched, but the efficacy and future success of Vertical AI hinges on the strength of its business models. Delivering your product in the right format for your specific vertical alongside a pricing model that captures the value you’re creating for customers is critical for the short and long-term viability of your business. In this installment of our Vertical AI Roadmap, we dive into three new business models defining the AI era — Copilots, Agents, and AI-enabled Services — and explore the innovative use cases and functions vertical AI companies are addressing today.
Copilots
The first incarnation of AI-native business models that we saw emerge were copilots. Copilots are AI applications that sit side-by-side with users as they go through workflows. In this way, AI copilots supercharge employee productivity while keeping the human user in the center of the workflow. Because copilots aim to increase individual employees’ efficiency and efficacy, copilots are generally priced like traditional cloud software on a per-seat basis tied to the company’s headcount.
This pricing model has already shown real momentum with public companies like Microsoft, Google, and Salesforce which have all been able to benefit from healthy price increases of their core products by offering copilot add-ons. For example, Microsoft’s Office365 generally costs $15 to $30 per license, but getting access to their copilot product costs an additional $30, doubling or even tripling the price per seat.
Copilot use cases by modality
Code: Github Copilot was one of the first widely adopted copilot applications in the market. Developers use Copilot to complete code, generate sample code, and ask questions, leading to productivity increases (reportedly as much as 55%) and higher developer job satisfaction. Our portfolio company Supermaven, which recently joined forces with Cursor, is another example. Its one million token context window understands a developer's code base and offers the best contextual code completion at lower latency, turning users into 10x more effective developers.
Text: Many text-based copilots assist or complete tasks for users within document-intensive workflows. For example, the AI copilot Harvey makes it easy for lawyers to quickly summarize contracts and get immediate answers to questions about specific content. Similarly, our portfolio company Sixfold AI helps insurance underwriters collate and synthesize information across sources to understand a prospective client’s risk profile.
Voice: As we discuss in part two of this series, significant, ongoing progress is being made on core components of the conversational voice stack. Advancements in speech-to-text models (automatic voice recognition), in particular, have supported a new generation of voice-based copilots addressing transcription use cases. These copilots “listen” to conversations, transcribe conversations, and often offer additional features, such as analytics or preparing and even helping users complete the next steps in a workflow.
Abridge is a company at the forefront of innovation in voice AI for clinical use cases. Its copilot product for healthcare providers transcribes, structures, and summarizes doctor-patient conversations, and writes clinical notes, which doctors can review and edit later. Abridge’s speech recognition technology can automatically detect the doctor’s specialty and the language spoken by the patient (across 28 languages), and translate in real-time to draft the clinical documentation in English.
Image: There are also AI copilots that generate images to streamline design processes in a variety of industries but are particularly becoming more prevalent in the architecture, engineering, and construction (AEC) industry. Workpack AI and Togal AI are visual copilots for estimators in the preconstruction process that automatically perceive, measure, and label project specs.
Agents
While copilots help employees do their work, AI agents fully automate workflows for specific functions with minimal human intervention required. In this way, agents are decoupling software and productivity from human headcount and transforming what businesses can achieve. Agent solutions are not only being built by vertical AI startups; incumbents are diving in headfirst, with Salesforce launching Agentforce, their employee and customer-facing support platform.
Pricing strategy for agents is still developing. Given that agents can substitute future incremental headcount and allow existing employees to work on higher value tasks, many are priced based on the solution’s output relative to human workers, and agent ROI is framed in terms of the money saved on expanding headcount.
Initial use cases for AI agents
Software sales: Relevance AI’s sales development representative (SDR) agent, Bosh, automates the process of identifying, researching, and contacting leads, and scheduling meetings.
Recruiting: LinkedIn recently announced the launch of its first AI agent Hiring Assistant, which takes on certain workflows typically done by recruiters, including sourcing candidates, turning notes into drafts of job descriptions, and more.
Customer support: Slang’s voice AI fields phone calls for restaurants, answering simple questions, making reservations, and connecting customers to employees as needed. Similarly, Assort Health’s AI agent call center for healthcare schedules patients appointments, reducing wait times and dropped calls.
Back office functions: Tennr automates document and referral processing, data entry, and other manual workflows related to healthcare administration.
AI-enabled services
By using software to automate work, AI-enabled services companies have the potential to deliver cheaper, faster, and more consistent services to the market and take share from incumbent services companies. Pricing for these services generally anchors to existing legacy service provider pricing, but, in many cases, automation allows AI companies to undercut existing providers and still retain higher margins, thanks to AI’s lower cost structure. For example, EvenUp charges per demand letters generated, which is less than the hourly pay required for an in-house paralegal to complete this work (and as a result, frees up paralegals to complete higher-value tasks.
Initial use cases for AI-enabled services
Legal services: EvenUp automatically builds demand packages for injury lawyers, allowing them to settle cases faster and more economically, and to sometimes win higher settlements than when all aspects of the workflow are done manually.
Medical billing: SmarterDx automates clinical documentation integrity (CDI) specialist work in hospital inpatient departments, analyzing 100% of the data contained in every patient chart to capture revenue that might otherwise be lost.
Third-party insurance administration (TPAs): Reserv automates the insurance claim process and delivers better data and insights to carriers, MGAs, and other partners. Reserve is able to compete with and often replace legacy TPAs like Sedgwick and Crawford by delivering superior service through the use of generative AI in addition to talent.
Early pricing model examples of emergent Vertical AI leaders
Among many breakout Vertical AI businesses, we’re seeing AI founders fully embrace usage and output-based pricing to align value capture with value creation. This approach of tying pricing to specific outcomes delivered means an easily quantifiable ROI for customers that can be benchmarked to their existing spend. In addition to this output-based pricing, vertical AI companies are often either putting this output into tiers or adding a base subscription fee to ensure a predictable baseline spend from each customer. This means that vertical AI companies can benefit from the predictability of subscription fees or tiered pricing while also capturing the upside of expanded use—a hybrid pricing represents an attractive model of value capture for vertical AI.
Company Company description Pricing model DeepL AI-powered translation company that provides highly accurate and nuanced language translation services for businesses and individuals Per user and editable file translation EvenUp AI-driven legal technology company that transforms the personal injury claims process by automating the creation of demand packages Per demand package generated by AI Intercom AI customer communication platform that launched an AI agent that handles frontline customer support autonomously FinAI agent with $0.99 per AI resolution FinAI copilot with 10 free tickets per agent Zendesk A customer service and engagement platform that helps businesses build better relationships with their customers Per automated ticket resolution
Up next: Our investment framework and founder advice
Vertical AI is a new frontier. While frameworks and strategies developed for horizontal AI and vertical software companies still have some utility for Vertical AI, we’re also seeing a significant (and growing) number of unique opportunities, challenges, and trends that founders will need to understand and contend with in order to build innovative and valuable vertical AI products and services, successfully bring them to market, and maintain defensibly in the face of competition from new AI upstarts as well as AI features from vertical incumbents who aren’t asleep at the wheel. In the fourth and final installment of our Vertical AI Roadmap, we’ll share our initial investment framework and founder advice focused on four core pillars of vertical AI products and businesses: functional value, economic value, competitive dynamics, and defensibility.
Bessemer Venture Partners has been fortunate to partner with legendary vertical software companies like Shopify, Procore, Toast, ServiceTitan, and MindBody — we think the next generation of vertical AI presents an even bigger opportunity. If you are working on a Vertical AI application, we would love to hear from you! Please reach out to our team at VerticalAI@bvp.com.
Contributors
Brian Feinstein
Partner
Brian is a partner in the San Francisco office and he focuses on investments in enterprise software. He is passionate about working with founders who are shaping their industries and often don’t fit the Silicon Valley mold.
Brian has been at Bessemer since 2008 and has invested in 5 companies that have gone public. Brian led the first institutional investments in Procore (IPO), Wildlife Studios, Restaurant365, Enjoei (IPO), and Ada, early-stage investments in Weave, Mambu, TractionGuest, and Clio, and growth-stage investments in nCino (IPO) and Bumble (IPO). Brian also led growth buyouts of LiveAuctioneers and Beyond.
During his time at Bessemer, Brian supported investments in Gainsight, Mindbody (IPO), Playdom and helped found Columbia Lake Partners, a European venture debt fund. Prior to Bessemer, Brian worked in the private equity group at Blackstone and founded an online advertising agency.
Brian graduated from Harvard University and sits on the board of the Heckscher Foundation for Children.
Caty Rea
Vice President
Caty Rea is a vice president based in Bessemer's Boston office and focuses on vertical AI, fintech and the business of sports.
Prior to joining Bessemer, Caty began her career at McKinsey & Company where she focused on advising tech companies as well as leading digital transformations for finance and insurance companies. Most recently, she was an investor focused on Series A through pre-IPO investments with Highland Capital Partners
Caty earned her MBA from Harvard Business School with honors and B.A. from Harvard College. In her spare time, she enjoys kayaking, reading, golf, and spending time with her husband, Ted, and dog, Mustard.
Kent Bennett
Partner
Kent Bennett is a partner in Bessemer’s Boston office focusing on B2B application software and consumer “earthquakes.”
Before his career in venture capital, Kent was a creative executive for an entertainment production company, where he developed and sold original material including a network television pilot and a feature film. He began his career with Bain & Co., where he worked on projects in industries spanning IT, retail, consumer products, healthcare, and biotech.
Kent earned an MBA from Harvard Business School, where he was a Baker Scholar, and graduated summa cum laude in systems engineering from the University of Virginia, where he was a Jefferson Scholar.
Byron Deeter
Partner
Byron Deeter is a leading investor in AI, Cloud, Frontier Technology, and the Business of Sports. He co-authored Bessemer’s iconic 10 Laws of Cloud Computing, the Bessemer Forbes Cloud 100, the BVP Nasdaq Emerging Cloud Index, and Bessemer’s STRIVE program for executive health and wellness. Byron works closely alongside many of the best founders in the cloud world, with 26 of Byron’s investments currently valued above $1 billion each, including 13 IPOs and counting.
Byron first raised a Series A with Bessemer back in 2000, as CEO and founder of Trigo Technologies. His company grew to be one of the first global SaaS companies, reaching profitability and was successfully sold to IBM. Byron foresaw that cloud computing would not only change the way people built new technologies but also how The Cloud would systematically run the world. In 2005, Byron returned to Bessemer, this time to help lead the firm’s global cloud practice.
Byron graduated with honors from The University of California, Berkeley, where he met his then college sweetheart and now wife. Byron is a perennial Midas List investor, past Chairman of the National Venture Capital Association, partner/owner of the San Francisco 49ers and Leeds United, as well as an active board member/advisor to numerous causes including the U.S. Olympic & Paralympic Foundation, U.C. Berkeley Foundation, Pledge 1% and Cal Rugby. Although he’s a four-time Rugby Collegiate National Champion and serial Ironman finisher, he’s largely converted to leisure sports of golf, wake surfing, and skiing with his wife and three children.
Sameer Dholakia
Partner
Sameer Dholakia is a partner of the growth investment practice at Bessemer, where he focuses on GenAI and Physical AI investments.
Before starting his second career in Venture Capital in 2022, Sameer spent 25 years as an operator, building software companies. His most recent role was as the CEO of Bessemer-backed, SendGrid, which he joined in 2014. He accelerated the company’s growth and led SendGrid through a successful IPO in 2017 and subsequent acquisition by leading cloud communications platform Twilio for approximately $3 billion in early 2019.
Before joining SendGrid, Sameer served as GM of the Cloud Platforms Group at Citrix, which he joined following its acquisition of his first startup, VMLogix.
Sameer earned a B.A. in economics and a M.A. in organizational studies from Stanford University. He also holds an M.B.A. from Harvard Business School.
Outside of work, Sameer most treasures his time with his wife, Laura, and their two kids. He enjoys traveling, watching sports, and trying to improve his golf game. He also supports philanthropic efforts at Pledge 1% and is the Board Chair of the Menlo School Board.
Mike Droesch
Partner
Mike Droesch is a partner in the Boston office primarily focusing on AI applications, cybersecurity, supply chain software, and B2B marketplaces. He currently serves on the board of directors for Tackle, Curri, Raft, Cypress, Netography, Optimal Dynamics, and VendorPM.
Previously, Mike worked with a few venture-backed startups in Boston, including two Bessemer portfolio companies, Fuze and InsightSquared, where he supported sales operations and analytics efforts. He started his career as a systems engineer and then spent nearly three years in management consulting at Navigant, where he helped companies build new businesses around emerging energy and infrastructure technologies in the U.S. and Middle East.
He holds an MBA from the MIT Sloan School of Management, a Master’s Degree in naval architecture and engineering from the University of Michigan, and a degree in mechanical engineering from Tufts University.
Maha Malik
Vice President
Maha is a Vice President in Bessemer Venture Partners’ New York office, where she focuses on early-stage investments across the application-layer. She partners with founders building across B2B, consumer, and prosumer platforms, with a particular interest in how workflows are being reshaped in the LLM era across verticals.
Prior to Bessemer, Maha was an Associate Partner at Bain & Company, where she focused on growth strategy, operations, new business incubation, and private equity diligence across software, consumer, and healthcare.
Maha graduated cum laude from Dartmouth College with a BA in Economics. She holds an MBA with distinction from Harvard Business School and a Master in Public Policy from Harvard Kennedy School. Originally from Pakistan, she loves traveling, experimenting in the kitchen, and writing.
Sam Bondy
Vice President
Sam is a vice president based out of San Francisco and primarily focuses on early and growth stage cloud and AI.
Prior to venture capital, Sam began his career in Technology, Media, and Telecommunications investment banking at J.P. Morgan where he focused on M&A and capital markets transactions for both private and public companies. He then joined Harvest Partners, a private equity firm in New York, focusing on software and business services buyout. Most recently, Sam moved into earlier stage investing where he worked at Soma Capital primarily focusing on software and fintech.
Sam grew up in New York City and first attended McGill University in Montreal, before graduating summa cum laude from SUNY Binghamton where he received a B.A. in Economics. Outside of work, he is an aspiring outdoorsman, a (very) novice golfer, skier, surfer, and loves to run, read, travel, and listen to podcasts.
Alex Yuditski
Vice President
Alex is a vice president with Bessemer’s growth investment practice where she primarily focuses on AI and cloud software investments.
Prior to joining Bessemer, Alex was an investor at Blue Owl Capital and focused on growth investments in 6sense, Brex, JumpCloud, Nuvemshop, Nylas, Kajabi, Klaviyo, Replicated, Robinhood, and Split. Prior to joining Blue Owl Capital, Alex was an investment banker in William Blair’s software M&A group and Regions Securities’ leveraged finance group.
Alex holds a bachelor’s degree in economics from Wake Forest University. Outside of work, you can find Alex cheering on the New York Giants, cooking, and spending time with friends and family.
Aia Sarycheva
Disclaimer: The information presented here is for general informational and educational purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation to buy or sell any securities or investment products. Certain companies discussed may be current or former portfolio companies of Bessemer Venture Partners. Past performance is not indicative of future results. All investments involve risk, including possible loss of principal.
