Vertical Team

Our History

At Vertical AI, our journey began with a simple but powerful vision: making AI accessible for everyone. We believe that the future belongs to those who can not only use AI, but customize it to their unique needs. Customization is the key that unlocks AI's full potential, transforming it from a generic tool into a personalized solution for every industry, every business, and every creator.

Our founder Mark, then an AI specialist in a real-estate firm, kept running into the same problem: Foundational AI models were incredibly powerful, but they often failed to meet the nuanced needs of specific industry verticals. An issue that not only occurred in real-estate, but in all industries. Watching non-technical colleagues struggle lit a single idea: give every professional the tools to customize and utilize AI, without the need to code like an AI engineer. That sketch on a whiteboard became Vertical AI.

Great ideas need allies, so Mark recruited a small crew of engineers and domain experts to start building out our first ideas. To bind early believers and build a community, we launched the $VERTAI token. All focused on one idea: making custom AI accessible for individual creators, and not just those who can afford developers. Hence we started developing our ecosystem of No-code tools for AI customization.

The Vertical Stream emerged first, born from a question: how do we reward creators who publish truly useful vertical models? The answer was a marketplace where creators of customized AI models earn every time their model is used, and users get a single window to access all frontier and custom models alike.

Since 2024, we had been actively developing the idea that started it all: a no-code tool for AI customization. In April 2025, that vision finally came to life with the beta launch of Vertical Studio. For the first time, our beta testers, ranging from small to medium-sized companies to creative individuals, were now able to customize AI models through fine-tuning and system prompting, entirely without the need for developers.

But customizing models at scale came with a major hurdle: GPU costs. From the start, we saw this as one of the biggest barriers to making AI truly accessible. Decentralized compute offered a cheaper path, but scaling it up and down like a traditional cloud was notoriously difficult, a core challenge we ran into early. The result was Vertical Cloud: a first-of-its-kind system that pools decentralized GPUs, fragments them, and auto-scales compute based on demand. It drastically reduces AI costs while staying fully scalable.