No-code developers can fine-tune AI models with ease — Here’s how

Vertical AI’s upcoming platform No-Code Studio will empower users from all backgrounds to fine-tune and integrate AI models.

Artificial intelligence has not taken over the world —at least yet— but, it has taken over a significant portion of business processes. According to PwC, 73% of US companies have already integrated AI into their business models, and a whopping 92% of companies worldwide plan to do so in the near future.

However, integrating the technology across diverse fields presents challenges that need to be overcome for widescale adoption. Different businesses require tailored AI solutions —which is the end goal of fine-tuning. Yet, the practice usually demands expertise in coding and machine learning, extensive computing power and significant financial investment.

Such restrictions result in tech giants dominating the AI market, making it difficult for smaller businesses and independent developers — who are left with generic AI models that may not align with their needs — to compete.

AI fine-tuning without coding

AI provider Vertical AI seeks to change this landscape by making fine-tuning more accessible and cost-effective with its latest initiative. Just launched as beta, Vertical Studio is a platform designed to remove the technical barriers associated with AI customization. Offered through an intuitive interface, the platform eliminates the need for programming knowledge and makes customization possible for a broader audience.

Unlike traditional no-code AI tools that only allow basic prompt adjustments, Vertical No-Code Studio supports real fine-tuning by letting users upload data sets and tweak parameters to modify model behavior at a deeper level. This ensures better alignment with specific use cases, improving accuracy and efficiency.

Creating custom AI models is difficult, especially for those without technical knowledge.

For this reason, AI creation is often out of reach for small companies and creative individuals.

So, we made our mission clear: We want to make it easy for everyone to train and deploy… pic.twitter.com/AHbmNbIGRY

— Vertical AI (@Build_Vertical) March 9, 2025

On the financial side, instead of relying on expensive cloud-based infrastructure, the upcoming platform leverages decentralized GPU networks. This results in broader access to computing resources and allows individuals and businesses to experiment with AI models by reducing costs and improving scalability.

Vertical Studio treads a fine line between Web2 and Web3 and integrates decentralized elements to where it adds value —as in the case of blockchain-based compute networks. Users and creators also have the option to pay for compute resources and monetize their AI models using cryptocurrency.

A customizable infrastructure

The orchestration layer, Vertical Cloud, scales the platform automatically and allows for enhanced customization. The network can automatically adjust allocated resources based on demand in real time.

Source: Vertical AI

Most cloud services require users to lease an entire high-end GPU, even in cases where a fraction is enough for the workload. Vertical AI’s GPU compartmentalization feature divides a single GPU into multiple independent workloads and lets users utilize only what they actually need.

Leasing procedures are also automated, and the platform leases and deallocates computing power dynamically. The entire system avoids wasting resources, significantly lowers costs for end-users and enables more flexible, on-demand access to high-performance AI training, making AI development truly affordable and accessible.

Platform soon to be released

Vertical recently launched its marketplace, Vertical Stream, where users can explore existing AI models and list their own models. The project just launched the beta of the Studio,  the v1 release of Vertical  Studio and the full launch of Vertical Cloud are slated for Q2 2025.

Source: Vertical AI

As AI adoption grows, the demand for customized models will continue to increase. Businesses, researchers and content creators will need AI systems that align with their specific objectives rather than relying on generic models that provide suboptimal results.

By streamlining the fine-tuning process and reducing infrastructure costs, Vertical AI is positioning itself as a platform that allows more organizations to integrate AI into their workflows. The future of AI depends on more than innovation; making model training accessible and practical is also vital for a wider range of users.