IVP’s Karthik Ramakrishnan: Navigating Disruption In Vertical AI SaaS

ABSTRACT

KEY POINTS FROM KARTHIK RAMAKRISHNAN'S POV:

Why is vertical AI SaaS such a compelling category moving forward? 

• Vertical software providers are uniquely able to capitalize on the high degree of trust they earn from customers to support critical workflows and, in turn, capture valuable data. This trust is built upon their deep understanding of industry-specific needs and their ability to provide tailored solutions for the core workflows of their customers. “Relative to horizontal software companies, vertical-specific solutions often have much greater access to the most important data and workflows of their customers. This could be transaction sales data from vertical embedded fintech solutions, or customer data from specialized CRM tools,” says Ramakrishnan.
• This access to critical customer data enables vertical AI SaaS companies to build industry-specific AI solutions that address multi-billion dollar end markets. “Vertical AI SaaS companies can leverage this data for AI models that address specific use cases in a way that large platform AI companies may not be able to," he adds. "This presents opportunities in many end markets that, despite not being large enough to capture the attention of large AI companies like OpenAI, still represent multi-billion dollar categories that can support massive Vertical AI SaaS outcomes."

What kinds of businesses or use cases might be attached to this category?

• Solutions for automated IP management and brand protection tailored to sectors including e-commerce, FinTech, and digital media. Traditional methods of managing intellectual property and combating fraud have been labor-intensive and inefficient. Counterfeited goods, for example, are a significant problem for many global fashion retailers and D2C companies. However, efforts to combat this issue have primarily been both manual and expensive. To combat this, companies would typically have to outsource to large agencies who would manually file takedown notices or reports for each specific instance of fraud. By leveraging advancements in AI and computer vision, companies like Doppel and MarqVision are pioneering automated solutions to detect and address counterfeit goods and fraudulent activities at greater scale and speed.  
• Sales and analytics tools that accommodate field sales teams in largely offline industries. “While software and digitally-enabled sales have become increasingly sophisticated over the past decade with platforms like Gong and Apollo, much of the U.S. economy is still driven by products sold out in the physical world”, adds Ramakrishnan. Examples include HVAC, home improvement, construction, and many variations of insurance and financial products. Field sales operations across these industries remain far less digitized than software sales teams. Companies like ServiceTitan and Podium have demonstrated the potential for success by providing CRM solutions tailored to the needs of field sales teams. Others, including Rilla and Avoca, are leveraging AI-driven analytics and communication automation to enhance sales performance and customer experiences in this domain.
• A new generation of vertical-specific design tools that support automation and collaboration in verticals like construction, architecture, and aerospace.  Traditionally, industries like architecture and construction have relied on legacy software solutions like AutoCAD and SketchUp. These solutions require substantial training to use and offer minimal features for collaboration amongst users. AI-driven platforms like Snaptrude are revolutionizing the design process by offering multiplayer collaboration and automation features, significantly speeding up workflows and improving productivity. “Many companies in this space are building much better alternatives to the traditional tools, and they are capturing very sticky customers.”

What are some of the potential roadblocks?

• Competing against established incumbents within these end markets requires a substantially superior product. Established legacy players enjoy significant market share, extensive resources, and longstanding relationships with customers. “Incumbents can leverage aggressive pricing strategies, channel partnerships, and bundled offerings to defend their market share. Breaking into such highly competitive landscapes necessitates a product that offers at least a 2x improvement in performance or value compared to incumbents," says Ramakrishnan.

IN THE INVESTOR’S OWN WORDS

Advancements in AI and machine learning have brought about a step change in the level of automation that can be achieved in many domains. This has opened the door for new solutions to address complex industry-specific workflows that have historically been very challenging to automate; either because they require coordination across many company stakeholders, different pieces of software, or both. There is tremendous opportunity for Vertical AI SaaS companies to disrupt the status quo within many verticals that represent substantial end markets.

Moreover, customer dissatisfaction with the legacy solutions for these verticals is at an all-time high. Many of these incumbents have undergone acquisitions or faced challenges due to macroeconomic factors, resulting in reduced focus on innovation and customer service. These converging factors have created a prime opportunity for startups to enter these markets with superior products and services, wedging into the market by optimizing a critical workflow and gradually expanding offerings to increase their coverage within customers’ business operations.  

Given the pace of innovation in this category, I believe that we will see a ‘land grab’ for market share over the next couple of years. As new companies emerge and move quickly in this space, there's a sense of urgency to seize market share. Early momentum can lead to a flywheel of rapid, enduring growth through word-of-mouth referrals alone, as businesses in these end markets are closely connected and tend to be very sticky customers relative to horizontal software categories. 

MORE Q&A

Q: How are emerging Vertical AI SaaS companies leveraging unique datasets to achieve significant performance improvements over existing legacy tools?

A: Vertical AI SaaS companies are capitalizing on the valuable data they gather from their customers right from the outset. By prioritizing automation in their product development roadmap, these companies are revolutionizing traditional workflows and processes that have long been manual and time-consuming. This strategic focus enables startups to offer levels of automation that were previously unattainable, distinguishing their products from incumbents. As automation capabilities continue to evolve at a rapid pace, many companies anticipate unlocking substantial time savings for their customers, potentially as much as 40-70%, with out-of-the-box capabilities.

Q:  What factors have contributed to the widespread dissatisfaction with legacy tools, and how are startups taking advantage of this environment?  

A: The innovator's dilemma is a recurring challenge for longstanding incumbents. As companies mature and establish leading market positions, their focus often shifts towards maximizing revenue and profitability, rather than continuous product iteration. This creates an opportunity for nimble startups to disrupt the market with innovative solutions. Startup teams, particularly those led by talented ML engineers, have the advantage of being able to ship products faster as they are unencumbered by the complexities of integrating with existing systems. Additionally, these teams are more attuned to the latest advancements in ML tooling and automation, enabling them to leverage cutting-edge technologies to drive rapid innovation. 

Q: What do other market participants often misunderstand about this category?

A: Many investors underestimate the unlockable value that many vertical end markets offer on a longer time horizon, and in turn, the total addressable market size of these end markets. When Vertical AI SaaS companies displace existing vendors, they create new opportunities to address additional workflows and to create and process greater transaction volume, thus expanding their growth potential significantly. While back-of-the-napkin calculations on the current value of potential buyers might not yield exciting numbers, a deeper look at the surface area that Vertical AI SaaS companies can gain with their customers at act three or four of the product roadmap can demonstrate the potential for large companies to be built very quickly. 

WHAT ELSE TO WATCH IN THIS CATEGORY

AI is poised to transform many time-intensive tasks in the product design process, resulting in design workflows that are increasingly multidisciplinary and collaborative. AI will increasingly be leveraged to automate user research processes, democratize design tools, enable more seamless design-to-engineering handoffs, and enhance the utilization of data in product design. As AI continues to redefine each of these workflows, improved collaboration, multidisciplinary thinking, and data-driven insight will become defining elements in the future of product design.  

Read more from Ramakrishnan on the impact of AI on product design, here.

STARTUPS MENTIONED IN THIS BRIEF

Avoca, Doppel, MarqVision, Podium, Rilla, ServiceTitan, Snaptrude

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