Alexander Kozenyevsky is involved in the development and maintenance of web projects, including edits and enhancements for websites built on various CMS and technology stacks. He specializes in virus removal and the identification and elimination of vulnerabilities. He develops applications using React, Tanstack, and NextJS, integrating Cloudflare and Supabase, and also implements solutions based on custom technical specifications.

Reviews

Alexander Kozenyevsky is a highly reputable performer, recognized by clients for his promptness, professionalism, and precise execution of tasks according to specifications. His work is completed quickly, often ahead of schedule, with high-quality results and without unnecessary questions. Reviews highlight his expertise in web development, including JS, CSS, and metric configuration, as well as his ability to tackle complex and unconventional tasks that other specialists have struggled with. Many clients commend his attention to detail, clarity, patience, and willingness to work without upfront payment.

However, one review mentions that Alexander may not be very communicative, although he himself denies this, emphasizing his quick response to inquiries. Despite this, no negative comments regarding the quality of his work or deadlines have been reported.

Portfolio projects

Skills and Technologies: web development, Tanstack, administration, working with Supabase databases, integration with external services, Cloudflare.

Projects and Achievements: development of an application for a beauty salon featuring a custom admin panel and personal account, which includes a notification system. The project incorporates synchronization of the masters' schedules with the external service Dikidi, enhancing appointment management and improving convenience for clients.

Achievements and Recognition: successful implementation of the project with minimal costs for the client, who only pays for the domain, demonstrating high efficiency in development and expense optimization.

* 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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