PCEase

Overview

Most PC-building tools are made for the US market with Newegg and Amazon.com prices. That's no help if you're buying in India. PCEase tracks prices from Amazon.in, Flipkart, MDComputers, PrimeABGB, and 5 more Indian retailers so you can actually compare what's available to you.

Besides price comparison, there's a full PC Builder with live budget tracking, wattage estimation, and bottleneck analysis. An AI Advisor powered by Gemini can recommend a complete build based on your budget and what you'll use it for. Plus community features like forums and shareable builds, all open-source and free.

Key Features

• Browse & filter 100+ components across 8 categories with grid/list views and inline vendor prices
• Price comparison across 9 Indian retailers with cheapest vendor highlighted and direct buy links
• PC Builder with slot-based build tool, live budget tracker, wattage estimator, and bottleneck analyzer
• Compare tool to place up to 4 components side-by-side with best values auto-highlighted
• AI Advisor: enter budget and use case to get a full build recommendation with interactive chat
• Community forum with threads, voting, and shareable builds via unique links

How It's Built

PCEase follows a clean three-tier architecture:

• Frontend: React 18 SPA built with Vite 5 and React Router v6. Component browsing, builder interface, and comparison tools with react-hot-toast notifications and Feather Icons throughout
• API Layer: FastAPI (Python 3.13) with Pydantic v2 for request validation. JWT authentication via python-jose, RESTful endpoints for components, builds, forum, and AI advisor features
• Compatibility Engine: Wattage calculator sums component TDP values and recommends PSU wattage with headroom. Bottleneck analyzer detects CPU-GPU tier mismatches before purchase
• Data Layer: PostgreSQL database with 100+ seeded components, 9 vendors, and 555+ price entries. Component prices tracked across all major Indian retailers

Interesting Challenges

• Price Data Aggregation: Tracking prices across 9 retailers with different data formats required a robust normalization pipeline to ensure consistent comparison and accurate "cheapest vendor" highlighting
• Build Sharing: Generating shareable build links without requiring user accounts. Builds are serialized and stored with unique share IDs for easy access
• AI Integration: Connecting the AI Advisor to generate contextual build recommendations based on budget and use case, with an interactive chat mode for follow-up questions

Screenshots