The rise of Vertical SaaS in the past decade has demonstrated the power of industry-specific software, producing dozens of winners like Toast, Shopify, Procore, and ServiceTitan.
Yet there are still many markets underserved by Vertical SaaS: foundational industries with intrinsic barriers to technological disruption (e.g. unstructured data, constrained TAMs, slow sale cycles, low annual contract values, and tricky incumbents), and sectors that are either just emerging or undergoing a major transformation (e.g. the electrification of energy.)
But now, two key developments have made it possible to build software that serves these outliers: 1) the rise of artificial intelligence that can tackle unstructured data and 2) the redefinition of Vertical SaaS as Vertical Software.
Starting with the data: In earlier tech eras, Vertical SaaS could only be applied to companies with modern tech stacks (those with clean, structured data in systems of record and databases).
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The concept of Vertical AI is fascinating and makes a lot of sense for creating AI solutions that truly address industry-specific challenges. It reminds me of how structured approaches, like analyzing a CCL Points Table, help streamline focus and optimize outcomes in competitive environments. Applying this kind of targeted strategy to AI development could definitely lead to more enduring applications.
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