PROJ_05

PROJ_05ACTIVE_DEVELOPMENTAI Systems / Educational Cloud Ecosystem

AETHERA

INTELLIGENT LEARNING & AI ASSESSMENT ECOSYSTEM

Aethera is a comprehensive cloud-native learning and AI assessment ecosystem. Deployed on AWS EC2 virtual machines backed by serverless AWS Lambda triggers and automated GitHub Actions CI/CD pipelines, Aethera combines an adaptive RAG Tutor (LangChain + vector embeddings), a real-time web IDE, computer vision malpractice detection in Java and Python, and low-latency encrypted WebRTC peer communication.

Launch Live Application GitHub Repository

TimelineMay 2024 – Present

RoleLead Fullstack & AI Cloud Architect

React.js///Next.js///WebRTC///Socket.io///Tailwind CSS///Framer Motion///LangChain///Vector Databases///OpenAI API///Semantic Search///Prompt Engineering///Node.js///Express.js///Python FastAPIs///JWT Auth///REST APIs///AWS (EC2, Lambda, S3)///GitHub Actions CI/CD///Docker///CloudWatch///React.js///Next.js///WebRTC///Socket.io///Tailwind CSS///Framer Motion///LangChain///Vector Databases///OpenAI API///Semantic Search///Prompt Engineering///Node.js///Express.js///Python FastAPIs///JWT Auth///REST APIs///AWS (EC2, Lambda, S3)///GitHub Actions CI/CD///Docker///CloudWatch///React.js///Next.js///WebRTC///Socket.io///Tailwind CSS///Framer Motion///LangChain///Vector Databases///OpenAI API///Semantic Search///Prompt Engineering///Node.js///Express.js///Python FastAPIs///JWT Auth///REST APIs///AWS (EC2, Lambda, S3)///GitHub Actions CI/CD///Docker///CloudWatch///

// SCREENSHOT SHOWCASE

IMAGE 01 / 03

aethera_view_1.pngCLICK TO EXPAND

PROJECT GALLERY (3 VIEWS)Click any thumbnail to switch view

Key Performance Metrics & Impact

Deployment Uptime

99.9%

Zero-downtime CI/CD releases on AWS EC2 & Lambda

RAG Retrieval Speed

< 250ms

Sub-second contextual response with vector embeddings

Proctoring Vision

Java & Python

Real-time automated code evaluation & malpractice detection

WebRTC Latency

< 45ms

Low-latency encrypted peer audio/video and messaging

Problem Statement

Traditional learning management systems lack contextual, personalized AI guidance, secure automated code assessment with malpractice prevention, and integrated real-time peer collaboration.

Engineering Solution

Architected a distributed fullstack platform uniting LangChain RAG vector retrieval, computer vision proctoring models, automated CI/CD deployment on AWS, and WebSockets/WebRTC for interactive code execution and peer study sessions.

Core Capabilities & System Features

Adaptive RAG Tutor & Web IDE

Contextual vector retrieval engine using LangChain and embeddings for personalized quiz generation and interactive documentation Q&A.

AI Proctoring Vision Pipeline

Automated vision evaluation pipeline detecting malpractice signals and evaluating code execution in Java and Python.

Skill Radar Analytics Dashboard

Multi-dimensional performance visualization mapping learner velocity, conceptual mastery, and code proficiency.

WebRTC Encrypted Peer Engine

Low-latency WebSocket & WebRTC peer mesh enabling real-time multi-user study rooms, media sharing, and video sessions.

Technical Stack Architecture

// Frontend & Realtime

React.jsNext.jsWebRTCSocket.ioTailwind CSSFramer Motion

// AI & LLM Pipeline

LangChainVector DatabasesOpenAI APISemantic SearchPrompt Engineering

// Backend Architecture

Node.jsExpress.jsPython FastAPIsJWT AuthREST APIs

// Cloud & DevOps

AWS (EC2, Lambda, S3)GitHub Actions CI/CDDockerCloudWatch

System Architecture Topology

TIER 1 // CLIENT INTERFACE & APPLICATION LAYER

PORTAL_ONLINE

Client Technologies:

React.jsNext.jsWebRTCSocket.ioTailwind CSSFramer Motion

Active Execution Modules:

G-Code Viewer & Code Diff Engine
Atomic Client State Hydration & Live Socket

HTTPS / REST / CRYPTO_HASH

TIER 2 // BACKEND ENGINE & SECURITY VAULT

VERIFIER_ACTIVE

Core Backend Stack:

LangChainVector DatabasesOpenAI APISemantic SearchPrompt Engineering

Security & Processing Pipeline:

AES-256 G-Code File Cipher & Audit Log Engine
Role-Based Access Controller (RBAC)

ENC_STREAM / GRIDFS_BINARY

TIER 3 // PERSISTENT STORAGE & CLOUD TIER

STORAGE_SYNCED

Storage Architecture:

Node.jsExpress.jsPython FastAPIsJWT AuthREST APIs

Data Persistence & Cloud:

MongoDB Atlas Machine Schemas & Operator Profiles
GCP Cloud Storage Encrypted Backup Vault

TELEMETRY_CONSOLE // aethera.sh

LIVE STREAM

>$ aethera-engine status --aws-cluster

>[SYS_HEALTH] AWS EC2 Instances: 2 Active | Lambda Handlers: HEALTHY

>$ aethera-engine rag query --topic 'Distributed Consensus in Go'

>[RAG_PIPELINE] Vector embedding matched in 185ms (Similarity: 0.94)

>$ aethera-engine proctor --eval-session live

>[VISION_PROCTOR] Signal scan completed: 0 Malpractice indicators

>[SUCCESS] Aethera intelligent learning ecosystem running.

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