MapleRewards
The first native Canadian credit card rewards optimizer. Maximize your cashback and points across 92+ cards and 19 loyalty programs — ranked by real dollar value, not just points.
Spend Optimizer Engine
The core of MapleRewards: tell it what you're buying, and it ranks every card by real dollar value returned — not just points. Supports base and business class redemption values, so you always know the true worth of your rewards.
AI Rewards Assistant
Powered by Claude Sonnet, the AI assistant answers any question about credit card rewards — from "best way to fly business class to London" to "maximize my points value." It understands your wallet and gives personalized advice.
Travel Redemption Calculator
Plan trips using your points. Supports Aeroplan, Amex MR, Avios, Marriott, Hyatt, Hilton, and IHG. Search flights and hotels with real-time availability, and see exactly how many points you need — with economy, business, and first class options.
Portfolio Analytics
See the total dollar value of your rewards portfolio, discover cards you might want, analyze annual fee ROI with breakeven calculations, and find the money you're leaving on the table with dollar-gap optimization.
Key Features
- Rewards optimizer ranking cards by effective return per category
- Wallet management with point tracking across 19 loyalty programs
- AI chat assistant powered by Claude Sonnet 4.5
- Trip planner with award flight and hotel search
- Portfolio analytics with fee ROI and dollar-gap analysis
- Welcome bonus tracking and personalized recommendations
- 92+ Canadian credit cards catalogued with live data
Tech Stack
Full-stack application with a Go backend serving 35+ REST API endpoints and a Next.js frontend. 27,760 lines of code across Go (10,717 LOC) and TypeScript (17,043 LOC). PostgreSQL with 12+ tables and 9 migrations, Redis caching layer, and JWT authentication.
In-Depth Project Detail
The Problem
Canadian credit card holders have no native tool to compare rewards across cards. American tools like The Points Guy don't support Canadian loyalty programs, and existing comparison sites only show earn rates — not real dollar values. MapleRewards fills this gap by being the first platform built specifically for the Canadian market.
Architecture
The backend is built in Go with the Chi router, chosen for its performance with concurrent API calls. PostgreSQL stores card data, user wallets, and spending profiles. Redis provides sub-millisecond caching for card lookups and optimization results. The frontend uses Next.js 16 with React 19 and server components for fast initial loads.
The Optimizer
The optimization engine calculates the effective return for every card across each spending category. It accounts for earn rates, point valuations (using both base and premium redemption values like business class flights), annual fees, and welcome bonuses. Users see a ranked list showing exactly how much real dollar value each card returns for their specific spending pattern.
Market Opportunity
No direct competitors exist in the Canadian market. The platform covers 92+ credit cards across all major issuers (TD, RBC, CIBC, BMO, Scotiabank, AMEX, HSBC) and 19 loyalty programs including Aeroplan, Scene+, PC Optimum, and Marriott Bonvoy. The SaaS model uses Stripe for premium features including advanced analytics and AI chat.