QuickPick AI - That Shops Smart, So You Don’t Have To.

Tired of wasting hours comparing gadgets and deals? QuickPick AI is your personal smart shopping assistant - just tell it what you need and it returns AI-curated product picks in seconds.

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Inspiration

Like many of us, I’ve often found myself endlessly scrolling through product listings, juggling 10+ tabs, reading reviews, comparing specs and prices, just to find the right gadget within my budget. Whether it's for a new phone, laptop, or smartwatch, this process is time-consuming and frustrating. I kept thinking, “What if shopping felt like texting your shopaholic bestie who knows your taste and nails it every time?”

This idea led me to build QuickPick, and the KIRO.dev AI Editor by AWS helped me turn that raw frustration into a product spec, fast.

What it does

QuickPick is an AI-powered shopping assistant that helps users make smarter product decisions in seconds.

Just describe what you're looking for in plain language, like:

  • “Laptop under ₹60,000 with good battery life”
  • “Smartphone with great camera and 5G under ₹15,000”

QuickPick instantly returns curated product suggestions from Amazon.in that match your budget, features, and intent, saving you hours of comparison research.

How I built it

The idea started during the AWS Hackathon using KIRO.dev, the AI code editor that helped me brainstorm, plan, and execute the project quickly:

  • 🧠 KIRO.dev generated my MVP specs after a few idea prompts
  • ⚙️ I built the backend with FastAPI + AWS Lambda, handling user queries and caching product search
  • 💻 Browser fingerprinting + IP detection for guest usage without login
  • 📦 Data pulled from Amazon product APIs and search endpoints
  • 💬 User inputs are parsed and enriched using AI prompt engineering, delivering personalized search responses

KIRO not only helped accelerate the spec-writing and code scaffolding, but it also kept me focused during rapid dev cycles.

Challenges I ran into

  • 🧪 Getting consistent, accurate product results with relevant filtering
  • ⚙️ Balancing response speed vs. rich data parsing
  • 👥 Designing a credit-based usage system for guests and registered users
  • 🧾 Creating structured product summaries out of unstructured eCommerce data

Accomplishments that I'm proud of

  • 🚀 Launched a fully working product in a week from idea to live website
  • 🎯 Users are already making real purchase decisions through the app

  • 📈 In just one day:

    • 50+ guest users
    • 150+ credit-based queries
    • 15+ purchase decisions triggered via AI recommendations

What I learned

  • ✨ A well-scoped idea, with AI tooling like KIRO, can dramatically accelerate product delivery
  • 🧠 People are excited to save research time and gain confidence in purchases
  • 🛠️ Small tools like browser fingerprinting, caching, and conversational prompts make a huge UX difference
  • 🤝 A single-person hackathon project can create real value with the right focus

What's next for QuickPick AI – That Shops Smart, So You Don’t Have To.

  • 🛍️ Expand beyond electronics into fashion, beauty, and home appliances
  • 🔁 Introduce AI-powered comparison, review summarization, and price tracking
  • 🌍 Add multi-language support for Indian regional users
  • 📦 Partner with other e-commerce platforms for broader product listings
  • 🧠 Enable personalized recommendations based on past queries
  • 🧪 Launch on Product Hunt, Reddit, and Discord communities to gather feedback and iterate faster

Let me know your thoughts or feedback and feel free to share it in your network. Your support means a lot 🙏

Thank you...

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