When we published "The State of Vertical SaaS" last October, most of the world had never heard of Large Language Models (LLMs). Only a month later, however, the public debut of OpenAI’s ChatGPT set in motion a vast transformation of the tech sector as a whole.
Within 2 months of its release, ChatGPT accumulated 100M Monthly Active Users, establishing it as the fastest-growing software application in history and the company behind it, OpenAI, is poised to achieve a $1B run rate within the upcoming year. The success of OpenAI and other generative AI companies underscores the tangible customer enthusiasm for AI-powered solutions and we are now witnessing the birth of novel product and service categories driven by this demand. Overall, LLMs have not just altered the fundamental paradigms of software development but have also reimagined how we interact with and harness the capabilities of software in our daily lives.
Although the LLM revolution has left no industry untouched, AI’s permeation into the software application layer is particularly apparent within vertical SaaS. The beginnings of what Index Ventures calls the “AI Platform Shift” has abruptly catapulted vertical SaaS into its next evolutionary phase, which is characterized by a race to integrate new AI-driven features into vertical workflow software.
In the midst of this AI-driven transformation of vertical SaaS and the broader tech sector, the Federal Reserve has persisted in its departure from a protracted period of Zero Interest Rate Policy (ZIRP). This transition has been characterized by an extended sequence of vigorous interest rate hikes which at the time of writing exceeds 5 percentage points. After a sustained period of prosperity marked by the culmination of the longest bull market in U.S. stock market history, it’s safe to assume that this year has been a sobering experience for most. In our corner, prevailing narratives surrounding VC markets and software industry valuations have been particularly sour. But, we believe that the fundraising environment we’re in today is much more sustainable than the unprecedented levels of 2020 and 2021. While public market SaaS multiples have seen a significant decline in the past 12 months, they’re now similarly aligned with the 5-year average between 2014-2018. In our view, the current environment is not an anomaly, but rather a return to the old normal.
The end of easily accessible, low-cost equity has forced a return to first principles thinking, where great companies are ultimately distinguished by their ability to achieve sustainable growth through operational efficiency, effective risk management, and strong business model fundamentals.
Despite macroeconomic uncertainties, we believe the advancements of LLMs present an enormous opportunity for vertical SaaS companies, especially those focused on systems of record (SoRs) for core workflows. These startups are best positioned to tap into the natural synergy between vertical SaaS and AI through their access to large proprietary industry and customer specific datasets that are critical for optimizing AI functionality. By targeting hyper-personalized pain-points with proprietary data, these startups are able to deliver optimized user solutions without unnecessary scope creep.
Businesses are held captive by fragmented software systems that force employees to endlessly switch between multiple applications—incurring the dreaded “toggle tax” on productivity. Overcoming this challenge has been a primary driver of the ascent of vertical SaaS platforms that provide unified, industry-specific solutions. Purpose-built for their niches, these vertical players crush pain-points and optimize operations with software solutions tailored to their customers’ exact needs.
These characteristics of vertical SaaS are also what continue to make it an attractive bet for investors. While raising capital hasn’t been easy this year, these solutions offer clear market opportunity, require lower Customer Acquisition Costs (CACs) due to their narrow customer segments, and have a tried-and-true business model that has minted several multi-billion dollar companies over the years.
Now, the LLM revolution and advancements in AI have amplified the appeal of vertical SaaS even further. With industry-specific data moats and dialed-in workflows, vertical players boast platforms that are inherently ripe for AI augmentation. Some of the most promising applications of AI in vertical SaaS include:
There's no denying that AI has already expanded the opportunities for vertical SaaS companies, but an important question remains: Which players are best poised to seize the multibillion dollar opportunity created by the AI platform shift? The current vertical SaaS landscape is a broad spectrum spanning antiquated legacy systems laden with technical debt to freshly minted AI-first point solutions. In our view, companies on either extreme of this spectrum aren’t optimally positioned at this time. Entrenched legacy providers face an uphill battle to modernize. Their aging architectures often intrinsically lack the flexibility needed to tightly integrate new capabilities. Retrofitting AI into these systems can prove an arduous and expensive endeavor, while compounding technical debt even further. AI-first solutions, on the other hand, lack the customer and industry datasets they need for optimized solutions.
Instead, we believe the vertical SaaS startups best positioned to leverage the potential of AI tools are somewhere in the middle: namely, the recent suite of vertical SaaS startups building true SoRs that provide a unified interface and a single source of truth across critical organizational workflows. In contrast to rigid legacy systems, they can adapt with agility to solve for evolving customer needs and market opportunities. And unlike narrowly focused AI point solutions, these companies offer comprehensive product capabilities that keep users engaged for longer and thereby gather growing amounts of valuable, proprietary workflow data.
By leveraging contextualized insights across their platform, SoR-focused vertical SaaS startups can strategically improve and expand upon their core products, while also incorporating stronger automation capabilities than their competitors. This initiates a positive feedback loop, where more usage generates more data to fuel better algorithms. Over time, we can anticipate these platforms growing into indispensable, automated Systems of Intelligence (SOIs) that are deeply integrated into customer operations.
Overall, the combination of rich vertical datasets, high customer loyalty, and an AI-augmented stack will be challenging to displace. Executing on these strengths enables vertical SaaS platforms forming best-in-class SoRs to outpace threats, whether from legacy incumbents or new entrants. From our perspective, these players stand at the cusp of an incredible opportunity to cement durable leadership through the intelligent integration of AI built upon their proprietary datasets.