We recently witnessed the adoption of AI models across various industries as companies are striving to enhance productivity and automate workflows. Major enterprise software companies and startups have quietly integrated AI into their platforms without the current intense hype. While there are a few exceptions, AI is not a standalone product. More often, it is utilized as a new layer of technology to enhance existing products.
The introduction of GPT-4 at the end of 2022 has brought AI to the forefront. There is hardly a week or day without new products launched by both industry giants and emerging players. Large language models (LLMs) swiftly gained ground, automating tasks in various sectors. While we and our companies have been experimenting and constructing AI models for quite some time, this sudden acceleration prompted us to think about it in a more strategic manner. We, at I2BF Global Ventures, are passionate about the impact of Generative AI on vertical SaaS (vSaaS) companies and our investment thesis.
The Rise of Vertical Software in the AI Landscape
Vertical software possesses a distinct advantage in the AI-driven landscape. Vertical players understand their target markets deeply, enabling them to deliver tailored solutions and gain a better grip on distribution and customer insights compared to their counterparts. AI and LLMs enable those players to create new and improved products, effectively addressing customer needs. The best industry-specific solutions seamlessly integrate into existing workflows, allowing vSaaS companies to gather valuable, inaccessible industry-specific data. This data further enhances their AI models, making their offerings even more effective. Let's dive deeper to gain a better understanding.
Cloud lessons
We can gain valuable insights into current trends from the cloud computing revolution (see our previous article). The cloud consists of two core layers: the infrastructure layer and the application layer. The winners in the infrastructure landscape include AWS, Azure, and GCP, who swiftly claimed a significant share of the market. The application layer has a more diversified landscape, with companies like Stripe, Twilio, Uber, and Airbnb accumulating substantial value. We observe similar trends in the AI domain. OpenAI, Antropic, and other key players dominate the infrastructure layer, while the application layer presents a more diverse terrain.
Vertical SaaS companies all possess a deep understanding of their end customers. They create comprehensive management hubs that offer tailored solutions to their customers (thanks TLV for introducing this useful term). Procore, ShopMonkey, Toast, Portside, and others serve as prime examples of platforms that provide a complete package, covering both the infrastructure and application layers. While they may not originate the infrastructure layer from scratch, they seamlessly integrate it into their offerings, delivering a holistic solution to customers. This approach aligns with our expectations for the future of Generative AI, where vertical SaaS platforms can leverage AI models to provide enhanced value to their customers.
We have already witnessed notable examples in our portfolio. For instance, Greywing has cleverly incorporated ChatGPT into their workflow, specifically in planning travel itineraries for ship crews during embarkation and disembarkation. Traditionally, this task has been far from exciting for operators. The ever-changing port schedules and the complex job of comparing flight expenses for multiple crew members heading in different directions presented a significant challenge. However, Greywing's integration of ChatGPT has streamlined the process, offering operators a more efficient and user-friendly solution.
The Data Advantage
One of the key defenses for vertical SaaS companies lies in their ownership of distinctive and proprietary data assets. They possess unique data that general-purpose LLMs often lack access to or cannot utilize effectively. This strategic advantage allows startups to craft their own AI models tailored precisely to their verticals. By leveraging the similarities across their customer base, these companies can apply the same models across various customers while still customizing them as needed. This differs from horizontal models, which may struggle with fine-tuning and customization.
As with any product, the user experience (UX) and user interface (UI) play a pivotal role. In this case, they are also of paramount importance. These models enable products with a seamless and delightful user experience that enhances value for both customers and end-users.
Our portfolio company, Parrot, develops a transcription platform for the legal and insurance industries. It streamlines the deposition process by using large language models (LLMs) for various sectors. The data captured during this process opens up opportunities to streamline other manual and time-consuming processes such as deposition reviews, demonstrating the potential for vertical SaaS companies to identify new avenues for growth.
So, what does the generative AI impact entail?
We believe that the current AI trend positively impacts the vertical portfolio and aligns well we with our strategy. We are optimistic about the potential of the future for vertical SaaS. The surge of innovation, driven by generative AI, will expand markets and facilitate adoption for vertical companies. We are always delighted to discuss your startup ideas. Please do not hesitate to connect with me on LinkedIn or via email (at korchevskiy@i2bf.com).