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Recently, shifts in both funding dynamics and technological advancements have unveiled a promising realm within the tech landscape: the vertical software stack. At N49P, we've been actively exploring this domain and are eager to share our insights on what we've observed and why we find it compelling.

Key Transformations in the Tech Ecosystem

In the past two years, we've witnessed two pivotal changes in the tech ecosystem:

1. Funding Realignment: A noticeable tightening in the funding landscape has prompted founders to reevaluate their strategies, emphasizing economic efficiency and earlier monetization in their entrepreneurial journeys.

2. The Rise of LLMs/Generative AI: The advent of Large Language Models (LLMs) or Generative AI has sparked the imaginations of countless entrepreneurs. This technology enables them to tackle problems in novel and more effective ways than previously feasible.

The Emergence of AI-First Startups

Among the plethora of startups, we've identified three primary archetypes within the AI-first domain. While the first two, foundational models and co-pilots, have garnered substantial attention and investment, a third model, which we term "Invisible Vertical AI," has remained relatively under the radar.

Understanding Invisible Vertical AI

This subset of startups leverages LLMs to streamline repetitive tasks inherent to specific verticals, tasks that often consume disproportionate amounts of time relative to their value.

Here's what sets these startups apart:

• Deep Industry Roots: Many of the founders hail from the industry or possess significant domain expertise, enabling a profound understanding of the problem space.

• Organic Adoption: Solutions resonate deeply with industry insiders who've long grappled with these challenges. The rapid uptake, fuelled by word-of-mouth referrals, translates to remarkably low Customer Acquisition Costs (CAC) and noteworthy virality.

• Focus on Invisibility: The goal is seamless integration into existing workflows or the elimination of cumbersome processes.

• Crucial Factors for Long-Term Success: Competitive advantage hinges less on technology and more on factors like seamless integration, effective distribution strategies, and leveraging unique customer data sets.

Early Adoption Dynamics and Growth Prospects

Interestingly, early adopters predominantly comprise Small and Medium-sized Businesses (SMBs) who swiftly recognize the tangible Return on Investment (ROI) in terms of time savings. While initial outcomes may not scream venture scale, we anticipate evolutionary paths that could reshape the industry landscape:

• Diverse Monetization Strategies: From performance-based pricing models to tapping into traditional Vertical SaaS revenue streams, there's ample room for innovative monetization approaches.

• Enterprise Penetration: As solutions mature, penetrating the enterprise market becomes a viable trajectory.

• Potential Industry Disruption: Over time, these solutions could challenge incumbent systems, reshaping entire workflows within industries.

Challenges and Opportunities Ahead

Founders in this space confront two primary challenges:

1. Market Validation: Until a few success stories emerge, securing venture capital may pose challenges. However, we anticipate these startups to exhibit remarkable capital efficiency, potentially requiring less funding to scale.

2. Playbook Innovation: Crafting new playbooks to fortify market positions and fuel scalability is imperative for sustained growth.

3. Evolution to enterprise-grade: The path that these companies take to be enterprise customers is not clear as AI brings several unique challenges around privacy and ownership of data that have to be resolved along the journey.

Our Endeavors at N49P

Learn more about N49P and how it’s supporting the tech ecosystem here

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