Pikadecks

PikaDecks is an AI-powered study platform available on web, mobile, and via MCP, turning PDFs, YouTube videos, and notes into smart flashcards with long-term retention.

Comment

PikaDecks: AI-Powered Learning Platform

Transforming Content into Knowledge

The Story Behind PikaDecks

Every student has experienced the same problem.

You attend lectures. Download dozens of PDFs. Watch YouTube tutorials. Read documentation. Highlight important paragraphs.

But when it's finally time to study...

You realize you've spent more time organizing information than actually learning it.

Creating flashcards manually takes hours.

Writing notes is repetitive.

By the time you're done preparing, you're already exhausted.

And even after all that effort, most of the information is forgotten within days.

This isn't because students don't work hard.

It's because modern education still relies on passive learning.

The Problem

Today's students face four major challenges.

1. Manual Knowledge Extraction

Educational content exists everywhere.

  • PDF books
  • Lecture slides
  • Research papers
  • YouTube videos
  • Documentation
  • Websites

Yet converting this information into effective study material is almost entirely manual.

2. Passive Learning

Reading.

Highlighting.

Watching videos.

Re-reading notes.

These activities feel productive, but they don't actively strengthen memory.

Students recognize information rather than recalling it.

3. Inefficient Revision

Most learners revise randomly.

Some topics receive too much attention.

Others are forgotten completely.

Without an intelligent review schedule, knowledge decays rapidly.

4. AI Cannot Interact With Learning Systems

Modern AI assistants can answer questions.

But they cannot naturally interact with learning platforms.

Imagine asking:

"Generate flashcards from this PDF."

or

"Save these cards to my Genetics deck."

Most learning applications cannot communicate with AI agents.

We wanted to change that.

Inspiration

One question inspired PikaDecks.

"What if studying required only understanding—not preparing?"

Instead of spending hours creating flashcards,

students should simply upload their learning material.

Artificial Intelligence should perform the repetitive work.

Students should spend their time learning.

Not organizing.

Our Vision

Our vision is to build an intelligent learning ecosystem where

every educational resource

becomes personalized study material within seconds.

AI should never replace learning.

AI should remove the friction around learning.

Introducing PikaDecks

PikaDecks is an AI-powered learning platform that automatically converts educational content into intelligent flashcards.

The platform consists of three integrated components:

  • Web Platform
  • Mobile Application
  • MCP Server for AI Assistants

Students can study anywhere while AI automates content generation.

⚙ Technology Stack

Frontend

  • React 19
  • TanStack Start
  • TypeScript
  • Vite

Mobile

  • React Native
  • Expo

Backend

  • FastAPI
  • Python

Database

  • PostgreSQL
  • Supabase

Storage

  • AWS S3

AI

  • Groq LLM
  • OCR
  • PDF Processing
  • NLP

Authentication

  • Clerk

Payments

  • Razorpay
  • Stripe

AI Integrations

  • Model Context Protocol (MCP)

AI Flashcard Generation Pipeline

The generation process is fully automated.

Upload PDF / Video
        │
        ▼
Extract Text
        │
        ▼
Clean & Chunk Content
        │
        ▼
Groq LLM
        │
        ▼
Identify

• Concepts
• Definitions
• Examples
• Comparisons
• Algorithms
• Formulae

        │
        ▼
Generate Flashcards
        │
        ▼
Store in Database
        │
        ▼
Sync to Web + Mobile + MCP

No manual copy-paste required.

Spaced Repetition Engine

PikaDecks uses a modified SuperMemo-2 (SM-2) scheduling algorithm.

Unlike traditional flashcard systems,

our scheduler adapts according to the learner's performance.

Each review updates:

  • Easiness Factor
  • Review Interval
  • Learning State
  • Due Date

Mathematical Model

Easiness Factor

The Easiness Factor determines how quickly review intervals expand.

\begin{cases} \max(1.3,EF_{old}-0.20) & Again\ \max(1.3,EF_{old}-0.15) & Hard\ EF_{old} & Good\ \min(3.0,EF_{old}+0.15) & Easy \end{cases}

Review Interval

For review cards,

\begin{cases} \max(1,\lceil I_{old}\times1.2\rceil) & Hard\ \max(1,\lceil I_{old}\times EF\rceil) & Good\ \max(3,\lceil I_{old}\times EF\times1.5\rceil) & Easy \end{cases}

Learning State

For newly learned cards,

\begin{cases} 5\text{ min} & Again\ 10\text{ min} & Hard\ 20\text{ min} & Good\ 4\text{ Days} & Easy \end{cases}

Once promoted,

the card enters the Review state.

Why This Works

PikaDecks combines two scientifically proven learning principles.

Active Recall

Instead of recognizing information,

students retrieve knowledge from memory.

Memory retrieval strengthens neural connections.

Spaced Repetition

Cards appear exactly before the learner is predicted to forget them.

This minimizes study time while maximizing retention.

Web Platform

The Web Application enables users to

  • Upload study material
  • Generate flashcards
  • Manage decks
  • Study with SRS
  • Track learning progress
  • View analytics

Mobile Application

The React Native application provides

  • Offline studying
  • Daily reminders
  • Sync with cloud
  • Review queues
  • Cross-device learning

Students can continue learning without internet connectivity.

MCP Server

One of PikaDecks' most innovative features is its Model Context Protocol (MCP) Server.

The MCP Server exposes learning capabilities directly to AI assistants.

Instead of manually interacting with the application,

users can simply ask:

"Generate flashcards from this lecture."

"Create a Biology deck."

"Save these cards."

"Show my learning statistics."

The MCP Server securely communicates with the backend and performs these operations automatically.

This allows AI assistants like ChatGPT, Claude, and other MCP-compatible clients to become intelligent study companions.

Challenges We Solved

AI Processing

Large PDFs require

  • OCR
  • Parsing
  • Chunking
  • AI Processing

We implemented asynchronous background processing with status tracking.

Offline Synchronization

Students often study without internet.

We designed an offline-first synchronization model where review history is replayed sequentially once connectivity is restored.

Multi-Platform Deployment

The project spans multiple platforms:

  • FastAPI Backend
  • React Web
  • React Native Mobile
  • MCP Server

Ensuring secure authentication and synchronized state across all services required careful architectural planning.

What We Learned

Developing PikaDecks demonstrated that AI is most powerful when integrated into the learning process rather than replacing it.

We also learned the importance of:

  • Modular system architecture
  • Asynchronous AI pipelines
  • Offline-first design
  • Cross-platform synchronization
  • Open standards like MCP for AI interoperability

Future Roadmap

Upcoming features include:

  • AI-generated quizzes
  • Voice learning
  • Image-based flashcards
  • Collaborative study groups
  • Classroom dashboards
  • LMS integrations
  • Multi-language support
  • AI tutoring
  • Advanced learning analytics
  • Additional MCP tools and integrations

Impact

Instead of spending hours preparing to study,

students can begin learning immediately.

Instead of memorizing temporarily,

they retain knowledge for the long term.

Instead of isolated learning,

they gain an AI-powered learning companion available across the web, mobile devices, and intelligent AI assistants.

Mission

PikaDecks exists to make learning effortless by combining Artificial Intelligence, scientifically proven memory techniques, and open AI integrations into one seamless learning platform.

One-Line Pitch

PikaDecks is an AI-powered learning ecosystem that transforms PDFs, videos, and notes into intelligent flashcards, delivers personalized spaced repetition across web and mobile, and enables seamless AI workflows through its Model Context Protocol (MCP) Server.

Built With

Share this project:

Updates