Project-Nexus

Multi-Tenant SaaS Data Collaboration Platform for Aerospace Engineering Teams

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🎯 Overview

Project-Nexus is a modern multi-tenant SaaS platform that bridges upstream data producers and downstream consumers in complex engineering environments (inspired by aerospace industry workflows).

It features a clean architectural separation between three core layers:

• Data Contracts — Upstream-owned governance and validation layer
• Goal Alignment & Monitoring — Downstream-defined expectations and intelligent monitoring
• Tasks & Workflows — AI-powered collaboration and proactive issue resolution

When deviations occur (even subtle ones), the system uses AI to detect them and automatically suggest or create actionable tasks — turning data into aligned action.

This project demonstrates enterprise-grade patterns highly relevant to Software Engineer II roles in aerospace and similar industries: multi-tenancy, clean architecture, domain-driven design, real-time collaboration, and AI integration in safety-critical domains.

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✨ Key Features (MVP)

Data Contracts Layer (Upstream Owned)

• Self-service creation and versioning of Data Contracts
• Define business goals, test variables, acceptable ranges, and quality rules
• Published contracts serve as the single source of truth for validation

Goal Alignment & Monitoring (Downstream Owned)

• Downstream teams define Alignment Expectations against published contracts
• Real-time monitoring of every payload against both the contract and all active expectations
• Severity levels (Warning / Critical)

Tasks & Workflows

• Kanban-style task boards for test campaigns and investigations
• Tasks automatically linked to Data Contracts, Payloads, or detected Deviations
• AI-powered task suggestion when anomalies are detected
• Real-time collaboration via WebSocket

Cross-Cutting Capabilities

• Strict multi-tenancy with Row Level Security
• JWT authentication + RBAC
• Async payload ingestion with RabbitMQ / AWS SQS
• AI deviation detection and insight generation (Spring AI + Groq/OpenAI)
• Audit trail and full traceability

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🏗️ Architecture

Core Design Principles:

• Clean Architecture + Domain-Driven Design (DDD) bounded contexts
• Strict separation between Data Contracts, Goal Alignment, and Tasks layers
• Production-grade multi-tenancy (tenant_id + PostgreSQL RLS)
• Event-driven async processing
• Context-aware AI features

High-Level Components:

• Frontend: React 19 + TypeScript + Tailwind CSS + shadcn/ui + TanStack Query
• Backend: Java 21 + Spring Boot 3 (Spring Data JPA, Spring Security, Spring WebSocket, Spring AI)
• Database: PostgreSQL 16 with Row Level Security + Redis
• Messaging: RabbitMQ or AWS SQS
• Storage: AWS S3 for payload files
• Deployment: Docker + AWS ECS Fargate + Terraform / AWS CDK

See docs/ARCHITECTURE.md for detailed architecture, data model, and data flows.

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📁 Project Structure

project-nexus/
├── nexus-backend/                  # Multi-module Spring Boot backend
│   ├── nexus-common/               # Shared entities, security, utilities
│   ├── nexus-contracts/            # Data Contracts bounded context
│   ├── nexus-alignment/            # Goal Alignment & Monitoring
│   ├── nexus-tasks/                # Tasks & Workflows
│   ├── nexus-ingestion/            # Async ingestion pipeline
│   └── nexus-api/                  # REST + WebSocket controllers
├── nexus-frontend/                 # React 19 + TypeScript SPA
├── docs/                           # Documentation
│   ├── BRD.md
│   ├── ARCHITECTURE.md
│   └── ...
├── infrastructure/                 # Terraform / AWS CDK
└── docker-compose.yml

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🚀 Quick Start

Prerequisites

• Java 21
• Node.js 20+
• Docker & Docker Compose
• PostgreSQL + Redis (or use docker-compose)

Backend

cd nexus-backend
./mvnw spring-boot:run

Frontend

cd nexus-frontend
npm install
npm run dev

Full Stack with Docker

docker-compose up --build

See docs/DEVELOPMENT.md (coming soon) for detailed setup.

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🛠️ Tech Stack

Layer	Technology
Frontend	React 19, TypeScript, Tailwind, shadcn/ui, TanStack Query
Backend	Java 21, Spring Boot 3, Spring Data JPA, Spring Security
Database	PostgreSQL (RLS), Redis
Async	RabbitMQ / AWS SQS
AI	Spring AI + Groq / OpenAI
Cloud	AWS (ECS Fargate, S3, RDS), Terraform / CDK
Other	Docker, JWT, OpenAPI, WebSocket

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📋 MVP Success Criteria

• Upstream teams can create & publish Data Contracts
• Downstream teams can define Alignment Expectations
• Payload ingestion with contract + expectation validation
• AI-powered deviation detection and task suggestion
• Strict multi-tenancy with Row Level Security
• Clean separation of concerns across layers

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🎯 Why This Project Matters

This repository showcases:

• Enterprise SaaS patterns suitable for mission-critical aerospace systems
• Multi-tenancy and strict data isolation (critical for cross-team / cross-program work)
• Clean architecture with clear domain boundaries
• AI integration that augments engineering workflows rather than replacing them
• Auditability and traceability essential in regulated environments

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📄 Documentation

• BRD.md — Business Requirements Document
• ARCHITECTURE.md — High-Level Architecture

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🤝 Contributing

This is a portfolio project built to demonstrate senior-level full-stack engineering skills. Contributions are welcome for learning purposes.

📬 Contact

Built by Chelsea Scott as a portfolio piece targeting Software Engineer II roles at aerospace and tech companies.

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⭐ Star this repo if you find it useful for your own learning or portfolio!

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Last updated: April 20, 2026