Why Vertical SaaS is the Launchpad for Emerging AI Companies 

By Ivan Nikkhoo 

Introduction 

As the AI hype cools, the spotlight shifts to real-world applications—and vertical SaaS (VSaaS) is emerging as the game-changer for AI startups. By targeting specific industries, VSaaS provides a proven path to product-market fit, measurable ROI and sustainable growth.   

The current state of flux within the venture capital market looks all but certain to continue into 2025. Unbridled AI hype has given way to sober reality, and a sizable cohort of fledging AI startups that found fundraising easy amidst the LLM explosion face a battle for survival in the year ahead.  

But while too many AI firms have been exposed as solutions searching for problems, there is a pathway emerging within vertical software-as-a-service (VSaaS) that signposts a profitable future both for founders, and the investors behind them.   

Vertical SaaS is the perennial overachiever 

Compared to the wider venture market, SaaS startups are well known for their lower failure rate across all stages of the growth journey. From an annualised return perspective, SaaS investments outperform the market from Series A onwards, indicating that once these startups achieve product market fit and make strides to generate high-quality revenue, they become very attractive prospects to VCs.  

Against this backdrop, the evolution of vertical SaaS – i.e. software solutions targeting specific industries – has occurred over three stages. First the cloud brought services online, then fintech enabled financial services to be embedded within the application, and now AI is enabling a transformation of service capabilities across various sectors.  

This third wave, which is the most impactful force in the category to date, further expands the surface area of vertical SaaS by turning Labor into Software. We are on the verge of a profound uplift in large enterprise efficiency and productivity, with AI ready to augment, automate away or, in some cases, replace many of the laborious, repetitive, routine tasks currently performed by people in areas like marketing, sales, customer service and finance.   

The ability to ingest data from disparate sources, normalise and structure that data, and make decisions based on that data are the cornerstones of this wave. This creates huge opportunities, and once again demonstrates why vertical SaaS – although perhaps less alluring than other areas of digital technology – will continue to offer fruitful terrain for startups who take the time and effort to get their approach right.  

AI is a perfect fit for enterprise data problems 

Operative Intelligence is a great example of a company that has succeeded in its vertical SaaS play, targeting the contact centre industry with a purpose-built AI product designed to help large organisations radically improve customer experiences. As CEO Peter Iansek explains, their target customers are being flooded with data across multiple business areas, making it very hard to derive meaningful insights about their performance.  

“Despite pumping huge sums of money into contact centres over the past decade, customer interactions have continued to increase, and customer experience levels have fallen lower and lower, largely because organisations don’t really know why customers are reaching out in the first place. There’s too much data and not enough actionable insight. Fortunately, parsing through huge data volumes, automating analysis and surfacing insights is something that AI is inherently well-suited to.” 

Once vertical SaaS AI companies start to establish a deeper understanding of their customers’ data, the possibilities for additional, more complex applications grow and grow, creating opportunities to expand and embed long-term relationships with some of the most valuable customers around. 

Time on the ground makes a big difference in vertical SaaS 

Operative Intelligence has seen high demand for its AI-powered contact centre analytics across multiple industries – from financial services and insurance to aviation and manufacturing.   

But Iansek is clear that the key to his companies’ success lies in the time they spent working in the contact centre industry prior to building their technology. “What matters in vertical SaaS is the specificity of the problem you’re solving. As former contact centre operators, we’ve experienced our customers’ issues firsthand. Our entire methodology was born from real-world experience. When we present to clients, the images in our decks come from actual centres we’ve worked with, which helps establish immediate credibility.” 

This is an important lesson for any AI company aspiring to enter the vertical SaaS arena. The general AI models that dominate the mainstream market today lack the industry or use case-specific context that large enterprises need to solve their trickiest data problems. Custom AI models are the key to unlocking this puzzle, but building an effective custom solution requires a deep knowledge of the problem you’re trying to solve.  

Real problems, measurable ROI  

Forward-thinking founders recognize that rather than trying to change the world with a general AI model sold as a be-all-and-end-all solution, the path to profitability, growth and future fundraising success in the current climate lies in solving high-impact problems in targeted industries.  

Budget holders in large enterprises have a mandate to invest in AI, but they want customised AI tools that deliver measurable value, not generic models that they don’t know where to deploy or how to realise ROI. 

The near-term future of AI isn’t just about creating new technologies but about solving real-world problems in a way that drives tangible, scalable value. It may not be glamorous, headline-grabbing work, but in 2025, we could well see some of the highest tech company valuations going to the AI startups that are able to make headway in vertical SaaS.

About the Author

With over 40 years of global C-level experience in tech, Ivan Nikkhoo is a seasoned investor, entrepreneur, advisor, board member, operator and educator. As the Founder and Managing Partner of Navigate Ventures, he leads a B2B Enterprise SaaS fund focused on entrepreneurs outside Silicon Valley between series A and B Growth rounds (A Extension Rounds).