Kirill Belyanski operates using the STAR model, focusing on results—creating fast, scalable products such as MVPs, services, or platforms capable of handling load and supporting business growth. He develops solutions using the Next.js and PayloadCMS stack, ensuring high speed, ease of content management, and the potential for future development without the need for rework. He pays close attention to architecture, integrations with CRM systems, payment processing, and 1C, writing clean code and creating autonomous products that do not rely on the client. The result is a reliable, stable, and cost-effective product that is easy to scale and allows the owner to fully manage their project.

Reviews

Kirill Belyanski is a qualified specialist who delivers work with high quality, efficiency, and often ahead of schedule. He demonstrates a high level of professionalism, shows initiative (for example, by suggesting improvements), and has a strong understanding of client needs, adapting solutions to specific requirements. He works on complex and large-scale projects, including the development of websites, landing pages, bots, and moderation systems. Feedback highlights his responsiveness, creativity, and willingness to engage in long-term collaboration. There are no negative comments in the reviews.

Portfolio projects

Skills and Technologies: web development, full-stack development, Node.js, React, Next.js, Strapi, Python, PyQt5, computer vision, PostgreSQL, API integration, payment system management, and bot development for Telegram.

Projects and Achievements: The candidate has developed several digital platforms, including a bus ticket sales service, a subscription platform for content monetization, and a website for analyzing athletes' movements in rowing. In the ticket sales project, a scalable system was created with payment integration and omnichannel communications, which reduced the load on ticket counters and improved the user experience. The subscription platform implemented a unified architecture for managing subscriptions and advertising placements, ensuring a user-friendly interface and process automation. The movement analysis project utilized modern computer vision algorithms, achieving high accuracy in analysis without the use of physical sensors.

Achievements and Recognition: The candidate successfully improved the structure and design of a kindergarten website, making it more intuitive and appealing to users. He also updated the BioRow.com website by implementing a subscription system and content protection, which contributed to audience growth and increased sales. The results of these projects include the creation of functional and user-friendly platforms that significantly enhanced business processes and user experience.

* It is created by a neural network based on a portfolio, information provided by the user about himself and reviews from other users.

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