Meet the bunq Purchase Advisor
Most banking tools help after money is spent. We asked: what if bunq could help users make smarter decisions before they buy? Impulse purchases, bad deals, and overlooked alternatives cost people money every day. We wanted to turn banking from expense tracking into purchase intelligence.
bunq Purchase Advisor helps users answer one simple question: Should I buy this?
How does the Purchase advisor work?
Users can scan a product, paste a URL, or enter a product manually. Our multimodal AI analyzes the item, compares alternatives and vendor pricing, considers spending context, and returns a clear recommendation:
BUY — good value, aligned with budget
WAIT — poor timing or likely better later
CHOOSE ALTERNATIVE — similar value at lower cost
Instead of only tracking spending after purchases happen, bunq can help optimize spending before it happens.
How we built it
We built the prototype with:
Next.js + TypeScript
React + Tailwind CSS
Anthropic multimodal AI
Product recommendation logic engine
Mock transaction/spending context integration
System flow:
Image / URL / Text Input → Product Analysis → Alternatives + Price Insight → Financial Recommendation
Biggest challenges:
- Keeping recommendations simple enough, but meaningful
- Differentiating “advisor” from generic shopping comparison tool
- Making AI feel trustworthy for financial decisions
- Designing something that feels natural to the bunq product experience
Main Lesson: Less complexity made the product stronger.
What's next for bunq Purchase Advisor?
Potential next steps:
- Real-time bunq account personalization
- Live merchant/vendor integrations
- Price history and “buy later” predictions
- Personalized financial goals-aware recommendations
- Agentic shopping assistant inside bunq
Long term, we see this as moving from expense management to financial decision intelligence.
Built With
- anthropic
- bunq-inspired
- multimodal-ai
- next.js
- react
- recommendation-engine
- spending-intelligence
- tailwind
- typescript
- vercel
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