Review-Saas System Requirements Document

1. Introduction

The project, Review-Saas, aims to develop a micro SaaS solution that automates the process of review mining for e-commerce sellers. This service will leverage AI to scrape reviews from platforms like Amazon and generate weekly sentiment and SWOT reports. The goal is to provide store owners with valuable insights that are typically offered by market researchers at premium rates.

2. System Overview

Review-Saas will be a cloud-based application designed to assist e-commerce sellers by automating the collection and analysis of customer reviews. The system will utilize AI to generate comprehensive reports that include sentiment analysis and SWOT (Strengths, Weaknesses, Opportunities, Threats) assessments. This will enable store owners to make informed decisions based on customer feedback.

3. Functional Requirements as Story Points

• As an e-commerce seller, I should be able to connect my store to the Review-Saas platform to start receiving review insights.
• As an e-commerce seller, I should be able to view weekly sentiment analysis reports generated from customer reviews.
• As an e-commerce seller, I should be able to access SWOT reports that highlight key strengths, weaknesses, opportunities, and threats based on customer feedback.
• As an admin, I should be able to manage user accounts and permissions within the Review-Saas platform.
• As an admin, I should be able to oversee API integrations and ensure data is accurately collected from various platforms.

4. User Personas

• E-commerce Seller: A store owner who uses the platform to gain insights from customer reviews.
• Admin: A system administrator responsible for managing user accounts and ensuring the platform's smooth operation.

5. Core User Flows

• E-commerce seller connects their store -> System scrapes reviews -> AI generates sentiment and SWOT reports -> Seller reviews insights
• Admin manages user accounts -> Admin oversees API integrations -> Ensures data accuracy and report generation

6. Visuals Colors and Theme

• primary: #1E90FF (Dodger Blue)
• primary_light: #63B8FF (Light Sky Blue)
• secondary: #FFD700 (Gold)
• accent: #FF4500 (Orange Red)
• highlight: #32CD32 (Lime Green)
• bg: #F5F5F5 (White Smoke)
• surface: #FFFFFF (White)
• text: #333333 (Dark Gray)
• text_muted: #777777 (Gray)
• border: #DDDDDD (Light Gray)

7. Signature Design Concept

Interactive Review Galaxy

The homepage will feature an interactive galaxy map where each star represents a review. Users can click on a star to open a detailed review card, drag to rotate the galaxy, and hover to highlight connections between reviews. This dynamic visualization will be built using @react-three/fiber and @react-three/drei to create an engaging 3D experience.

LANDING HERO MOTION BRIEF

The landing hero will depict a flow of reviews gathering around a central AI engine. As the reviews enter the engine, they transform into a vibrant report that displays key insights. This animation will loop continuously, using motion/react for smooth transitions and interactions. The composition will feature layers of reviews, the AI engine, and the resulting report, creating a visually compelling narrative.

8. Interaction Model & Motion Direction

• Interaction Model: Parallax
• The landing page will utilize a parallax effect to create a sense of depth, with layers of reviews and insights moving at different speeds. This will enhance the storytelling aspect and provide a visually rich first impression.

9. Non-Functional Requirements

• The system must ensure data privacy and comply with relevant data protection regulations.
• The platform should be scalable to handle an increasing number of users and data volume.
• The application must provide a responsive design that works seamlessly across devices.

10. Tech Stack

• Frontend: React for Web
• Backend: Python, FastAPI
• Database: MongoDB
• AI Models: GPT 5.4 for user-friendly responses
• AI Tools: Litellm for LLM Routing, Langchain
• Local Orchestration: Docker, docker-compose
• Server-Side Orchestration: Kubernetes

11. Assumptions and Constraints

• The system assumes that e-commerce sellers have access to their store's API for integration.
• The platform is constrained by the data access policies of third-party review platforms.
• The application will operate primarily in the Indian market, considering local currency and timezone settings.

12. Glossary

• SaaS: Software as a Service
• SWOT: Strengths, Weaknesses, Opportunities, Threats
• API: Application Programming Interface
• AI: Artificial Intelligence
• LLM: Large Language Model

This document outlines the requirements and design for the Review-Saas project, ensuring a comprehensive understanding of the system's capabilities and design direction.