PCEase

Overview

Most PC-building tools target the US market with Newegg/Amazon.com pricing. PCEase is built specifically for Indian buyers — tracking prices from Amazon.in, Flipkart, MDComputers, PrimeABGB, and 5 more retailers. Browse 100+ components, compare prices side-by-side, and build custom PCs with real-time compatibility checking.

Beyond price comparison, PCEase includes a full PC Builder with live budget tracking, wattage estimation, and bottleneck analysis. An AI Advisor powered by Gemini recommends builds based on your budget and use case. Community features like forums and shareable builds round out the platform — 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