QSPK Interactive Widget Builder

QSPK smart widgets service

Marketing service for creating interactive button-based dialogs for websites and social media

Viacheslav Ustinov
Viacheslav UstinovFullstack: Next.js, Zustand, FastAPI, Django, Postgre, Redis, Kafka

Marketing tool for quickly creating interactive button widgets with built-in conversational AI

Platform for instantly creating lightweight, visually striking button widgets with intelligent conversational AI, used in gamified landing pages and interactive modules; engages cold traffic, retains attention, and delivers high conversion for complex services and bespoke offers.

Marketing tool for quickly creating interactive button widgets with built-in conversational AI

About the application architecture

The application is built on a multi-layered monolithic architecture. This means that although the entire service is a single unit, its internal structure is clearly divided into logical layers. This separation of application parts by technical cohesion promotes encapsulation and reduces dependencies within the monolith. Additionally, a modular approach is used for some added features, allowing new functional blocks to be integrated relatively easily without disrupting the core system's stability.

This choice was made due to the service's compact size and clear boundaries of its technical features. There's no need for the complexity of distributed systems when the monolith handles current tasks. Extensive system evolution is not required in this context. Instead, exceptional application testability, transaction control, simplicity, and development speed are crucial. These criteria are ideally suited for a monolithic structure, where code is only separated by technical concern.

Alongside this, the service includes several independent components, which handle heavy computations and a number of slow operations.

Simple integration with built-in AI

The service integrates easily into any web application, includes an AI builder for project automation, and an AI component for user conversations beyond button interfaces. Simple for everyone to use.

Simple integration with built-in AI

More details about the backend

The backend is built on Django, DRF, PostgreSQL, Redis, and Celery with separate FastAPI microservices—enabling rapid development, a built-in admin panel, and scalability, while asynchronous tasks boost performance without overloading Django.

About the frontend

The main application modules and user account are implemented using React 18–19, Next.js, and Zustand; an auxiliary TypeScript service built with Vite has been created for the widgets.

About the frontend
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Collaborating with agencies, businesses, and in-house teams

If necessary, I can involve designers, data analysts, and senior-level developers in the project

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About me: portfolio, tech stack, working conditions, experience