Analyzing over 200 investments, TinySeed observed that vertical SaaS companies consistently achieve stronger exits, grow further, and have lower churn than horizontal SaaS. This data-driven insight has shifted their investment thesis toward more defensible, niche-focused companies, as they have proven to have distinct advantages.
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Pendo's CPO explains that while vertical products (e.g., for banking) can gain deep insights from a small user group, horizontal platforms must develop discovery processes that can handle immense complexity and scale across diverse industries and maturity levels.
The founder predicts that hyper-specific vertical AI solutions are too easy to replicate. While they may find initial traction, they lack a durable moat. The stronger, long-term business is building horizontal tools that empower users to solve their own complex problems.
Horizontal SaaS companies fracture their customer knowledge across diverse industries, forcing generic messaging. Vertical SaaS companies build compounding knowledge with each customer within a niche. This leads to deeper insights, stronger competitive secrets, and more effective, specific messaging over time.
Most SaaS startups begin with SMBs for faster sales cycles. Nexla did the opposite, targeting complex enterprise problems from day one. This forced them to build a deeply capable platform that could later be simplified for smaller customers, rather than trying to scale up an SMB solution.
While platform businesses (marketplaces) can achieve massive valuations, they are incredibly difficult and expensive to build due to the chicken-and-egg problem. For most founders, a traditional B2B SaaS model is a far safer and more direct path to success.
A key trend TinySeed observes among AI-focused applicants is extremely high churn, often 10-20% per month. Even with rapid top-line growth, this level is deemed "catastrophic," indicating many new AI products struggle with defensibility and long-term customer value, making them risky investments despite the hype.
A smaller fund size enables investments in seemingly niche but potentially lucrative sectors, such as software for dental labs. A larger fund would have to pass on such a deal, not because the founder is weak, but because the potential exit isn't large enough to satisfy their fund return model.
Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.
YC Partner Harsh Taggar suggests a durable competitive moat for startups exists in niche, B2B verticals like auditing or insurance. The top engineering talent at large labs like OpenAI or Anthropic are unlikely to be passionate about building these specific applications, leaving the market open for focused startups.
The company became a breakout success by targeting a specific high-value niche (doctors needing research), building a tailored LLM product for their workflow, and creating a perfect monetization loop with targeted advertisers (pharmaceutical companies) who need to reach that exact audience.
