Pavel Gasanov

Camcorder AI is an AI-driven video editing SaaS platform designed to simplify content creation through features like automated storyboarding, semantic video trimming, smart media matching, instant voiceover generation, and platform-ready exporting. The platform enables creators to rapidly transform raw footage into polished, platform-optimized videos with minimal manual editing.

I was responsible for the full-stack development of the entire application, from architecting the back-end APIs and real-time video processing pipelines to designing and implementing the front-end user experience. My work included integrating AI models for media analysis and voice synthesis, building scalable infrastructure to handle thousands of concurrent users, and ensuring smooth performance across browsers and devices. I collaborated closely with design and product teams to translate requirements into intuitive workflows, reducing video rendering times by 40% and helping the platform onboard over 5,000 active users in its first months.

Icowork helps people find, book, and review workspaces, offices, meeting rooms, and conference halls.

As the website's full-stack developer, I changed its front-end redesign using a Figma layout, added server-side rendering to support SEO processes, and implemented multiple features. These improvements ultimately made the website one of the top three coworking aggregators in the Russian segment.

Simple, all-in-one eCommerce solution designed to launch and grow their online sales quickly. I was responsible for converting the site from Gatsby to Nextjs, connecting to Sanity CMS. I also led a redesign and several quality-of-life improvements.

A React-based CRM for audio artists and creators. I was in charge of creating both the back end, front end and converting XD to pixel-perfect layout using MUI components. Additionally, I changed the main landing page and developed several features.

Project ROI's website is a place for Russian dividend investors to share their knowledge and ideas. It was built using Laravel, PHP, and MySQL.

The main feature I implemented is a private cabinet for videos, articles, and useful Google Sheets that members of the club can access. The website is powered by IEX Cloud, the Telegram Bot API, and a curated list of stocks that members can consult to make informed investment decisions.

A back-end API for providing Shortdeck poker hand odds calculation. The core logic is based on https://github.com/julianandrews/pyeval7 with several changes to work only for Shortdeck rules. I also added a front-end page to the WordPress website using the client's Figma design.

Correspondence.legal is a professional profile site for attorneys. I built it from scratch using Django with Vue.js components to improve user experience. I managed a team of three developers and one designer.

"AI as your co-writer" is the slogan, suggesting that people "upload your unaccompanied solo or stem and let our algorithms recognize notes and recommend the meter and harmony that fit best your performance."

I was the full-stack developer responsible for creating distributed infrastructure and helped to implement a cloud-based parser.

A dating social app, written in Vue.js and Django REST framework, then deployed using AWS CloudFormation. I was responsible for adding multiple features, such as changing the matching algorithms, adding timeline support, and updating the design to match Figma mockups.

The Gateway project incorporated a Python integration between the eCommerce system and multiple popular open-source eCommerce shops. The integration included syncing product variants, images, SKUs, and prices in different currencies. I was a back-end developer working on several integrations, including Prestashop, Magento, and IdoSell.

This project involved scraping data from nine major Australian eCommerce websites using Scrapy. I created the pipeline and the different spiders for different data sources. Scrapers were run from Amazon Elastic Compute Cloud (Amazon EC2) instance, stored data in AWS S3, and sent daily reports to emails using AWS SES.

A dashcam software that utilizes machine vision to evaluate driver performance. It was written in Python with OpenCV and pytorchcv. I was in charge of developing image recognition and communication modules.