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EdTech & Spring AI RAG

Cholo Sikhai

AI-native EdTech platform featuring a modular Retrieval-Augmented Generation pipeline implemented in Java and Spring Boot.

Context / Event

The Infinity AI BuildFest 2026 (CloudCamp Bangladesh)

Category

EdTech & Spring AI RAG

Published Date

June 2026

AI Framework

Java Spring AI RAG

01. The Problem & Challenge

The Problem & Real-World Friction

Modern AI tutoring systems often rely on Python backends, making integration with enterprise Java architectures challenging while struggling with domain hallucination.

02. The Engineered Solution

Architectural & Technical Approach

Co-developed an AI-native educational architecture featuring a modular RAG pipeline implemented directly in Java using Spring AI, designed with architecture for future agentic AI and Model Context Protocol (MCP) integrations.

03. Core Capabilities Breakdown

Key Technical Highlights

Java Spring AI RAG Education Architecture

Enterprise Java Spring AI Pipeline

Native Java implementation of Retrieval-Augmented Generation using Spring AI, integrating directly with enterprise Java architectures.

Grounded Vector Similarity Search

PostgreSQL pgvector similarity search indexing educational textbooks and lecture notes with cosine distance scoring.

Hallucination Reduction Safeguards

Enforces strict document retrieval boundary constraints to eliminate generative hallucinations in STEM course tutoring.

Agentic MCP Tool Extensibility

Architected for future Model Context Protocol (MCP) tool integration to enable automated quizzes and interactive problem solving.

04. Measured Outcome & Impact

Project Results & Impact

Developed for The Infinity AI BuildFest 2026 (CloudCamp Bangladesh), proving enterprise Java/Spring AI suitability for grounded LLM retrieval.

Technologies Used

6 tools
JavaSpring BootSpring AIRetrieval-Augmented Generation (RAG)REST APIsPostgreSQL
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