Case Study: Preplance – AI-Powered Exam & Interview Preparation Platform

Role: Full-Stack Developer

Introduction

Preplance is a cross-platform mobile app designed to help users prepare for technical and government exams with smart mock tests, AI-driven interviews, and previous year paper analysis. The platform provides a seamless learning experience enhanced by DeepSeek AI integration, Speech-to-Text (STT), and Text-to-Speech (TTS) technologies for real-time interactive practice.

Platform Components:

  • Mobile Learning App: Cross-platform app allowing users to practice mock tests, attend AI-driven interviews, and review previous exam papers with instant feedback.
  • AI Mock Interview System: DeepSeek AI integration for conducting realistic interview simulations with dynamic question generation and performance analysis.
  • Test & Paper Module: Enables users to attempt topic-wise and year-wise tests for structured preparation and detailed result insights.
  • Backend API: Node.js and Express backend providing secure APIs for managing users, tests, AI sessions, and progress analytics.
  • Voice Interaction: STT and TTS features implemented for natural AI conversations and accessibility during mock interviews.

Technology Stack

Frontend Technologies:

  • Apache Cordova: Used for cross-platform mobile app development on Android and iOS.
  • React.js: Enabled dynamic rendering, responsive UI components, and state management for an interactive experience.
  • JavaScript + HTML5: Provided the foundation for building interactive app logic and UI structures.

Backend Technologies:

  • Node.js + Express: Developed RESTful APIs to handle authentication, tests, and AI interview sessions.
  • DeepSeek AI Integration: Powered AI-driven mock interviews and intelligent feedback through NLP-based models.
  • Postgres: Used for scalable data storage of users, tests, and AI session logs.

DevOps & Infrastructure:

  • Cloud Deployment: Deployed backend services on Vps ensuring uptime and performance.
  • Security & Authentication: Implemented JWT authentication and HTTPS encryption for user data protection.

Detailed Breakdown:

Preplance Mobile App

An AI-assisted exam and interview preparation app that helps users practice mock tests, analyze results, and attend interactive AI interviews. Built with Cordova and React.js for cross-platform support and enhanced with STT/TTS for hands-free interaction.

Technologies Used: Apache Cordova, React.js, JavaScript, HTML5, Tailwind CSS, CSS3

Download APK
Preplance Mobile App GIF

Preplance Backend API

Node.js and Express backend powering Preplance’s AI-driven learning modules. Features secure APIs for test management, AI interviews, and user analytics, integrated with DeepSeek AI for real-time conversation and performance evaluation.

Technologies Used: Node.js, Express.js, Postgres, DeepSeek AI, REST API

Visit Site
Preplance Backend API GIF

My Role

  • Full-Stack Development: Built the complete application stack, including mobile UI, backend API endpoints, and AI integrations.
  • AI & Voice Integration: Integrated DeepSeek AI along with STT/TTS features to enable interactive and voice-based learning.
  • Test & Result Module: Developed dynamic test generation, result analytics, and progress tracking components.
  • Backend Architecture: Designed RESTful APIs and Sql schema for secure and efficient data handling.

Challenges & Solutions

Challenge 1: Implementing natural AI conversations for mock interviews

Solution: Integrated DeepSeek AI with contextual memory and voice interface using STT/TTS APIs for realistic user interaction.

Challenge 2: Managing large-scale test data and user analytics

Solution: Optimized Sql queries and implemented pagination and caching mechanisms for fast response times.

Challenge 3: Ensuring smooth cross-platform performance

Solution: Used Cordova plugins for native optimization and React’s virtual DOM for smooth UI transitions.

Lessons Learned

  • AI Integration Elevates Learning Experience: Adding conversational AI transformed standard mock tests into dynamic, personalized learning sessions.
  • Voice Features Enhance Accessibility: Implementing STT/TTS improved usability and engagement, especially for hands-free learning.
  • Modular Architecture Simplifies Scaling: Separating AI logic, test modules, and backend APIs made future updates and maintenance effortless.

Conclusion

Preplance successfully merges AI, voice interaction, and smart test analytics to redefine exam and interview preparation. The cross-platform design, secure backend, and DeepSeek AI integration make it a modern, scalable, and engaging solution for learners across domains.