Our goal has always been to make AI customization accessible to everyone. As we are also blockchain fanatics looking to harness the power of decentralized networks, our original name, NIM Layer, suited us fine. The No-code Innovation Machine that served as an application layer built with blockchain technology. This sounded awesome, but was too crypto oriented for the direction we are heading towards.

The deeper we dig and the closer we get to finishing our MVP, we realize we are building something that is quite rare in the market. Our mission is focused on making AI available to a wider audience across different industries. For that reason, we decided to evolve into a more mature brand with a fresh name that more people can relate to.

“To improve is to change; to be perfect is to change often.” - Winston Churchill

Why Vertical fits us so well

Some foundational models, like GPT or Llama, are “horizontal” types, meaning they are designed to handle a wide range of tasks. Also known as foundational models, these models aren’t specialized for a single job but can answer questions, generate content, and support customer service in almost any field. Because they’re so broad, they can help businesses in different ways without being specifically tailored for one industry. However, they sometimes fall short when tasks get too specific.

This is where ‘vertical’ models come into play. By training a foundational model in a specific direction, it becomes a ‘vertical’ AI model with a more industry-specific focus, specialized in assisting with a particular task. As these models have deeper domain knowledge and use specialized algorithms, they often offer more significant results and a better return on investment (ROI). We want to enable you to create your own ‘vertical’ model with just a few clicks. To emphasize this goal, our name needs to point in the same direction.

Creating something really special

After diving into extensive research, we truly understood that what we are building is unique. Even a platform like Hugging Face, which is praised for its ease of use and accessibility, is still hard to understand for non-technicals. What differentiates our platform is the removal of these technical barriers. Vertical AI will allow the creation, tuning, and running of models in an intuitive drag-and-drop interface. No more need for finding all the resources, reformatted datasets, finding the right models to tune, reading docs with technical lingo you don’t understand, and installing unknown dependencies (assuming you even know how to use the CLI).

Our mission is clear: we want everyone to be able to participate in the AI revolution. We are building this for creators, not engineers. We’ll make sure all the hard stuff is done in the background, so that creators can focus on improving the quality of their data and output.

Meeting a market need

Undeniably, there has been an increasing need for AI solutions that are designed for particular industries, but plenty of businesses struggle as they do not have dedicated technical resources or expertise. For this reason, AI creation is often out of reach for small companies or individual creators. By making it easier for everyone to build, deploy, and use “vertical” AI models, we’re helping users and businesses of all sizes integrate AI models into their workflows and applications. This creates new opportunities and allows everyone, from individuals and small businesses to large enterprises, to optimize their products with ease.

Moving forward: What we envision for Vertical AI

Vertical AI will not just be a platform but an entire ecosystem that enables everyone to join in on the AI revolution. Our vision is of an AI future that is driven by creators and not just by engineers. In our ongoing evolution, we will continue to deliver on accessibility, scalability, and simplicity. We believe AI verticalization is the future, and we are proud to be a part of this.