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PROJECTS LAB

Engineering Chambers

Deep-dive into each project — architecture, decisions, and implementation details.

Lexora AI

RAG-Powered Knowledge Platform

2025

Lexora AI is a production-grade knowledge platform built around a custom RAG (Retrieval-Augmented Generation) pipeline. It features a multi-tenant architecture that allows different organizations to maintain isolated knowledge bases while sharing the same infrastructure.

The system leverages Qdrant for high-dimensional vector search, enabling semantic retrieval with sub-200ms query latency. Documents are processed through an intelligent chunking pipeline, embedded using OpenAI's text-embedding-3-large, and stored with rich metadata for precise retrieval.

ARCHITECTURE LAYERS
Client
Next.js App
React UI
API
FastAPI
Auth Middleware
Rate Limiter
AI Core
OpenAI Embed
RAG Pipeline
Chunker
Storage
Qdrant
PostgreSQL
Redis Cache
< 200ms queryMulti-tenantVector search
Next.jsQdrantPostgreSQLOpenAIPython