88% of business cards are thrown away within a week.

The average professional collects 200+ business cards per year. That's 176 contacts lost. If even 10% could've been valuable connections, we're talking about massive opportunity cost.

I got obsessed with this problem after watching my own business card graveyard grow. Built a real-time networking platform (Yenhyia) that makes business cards irrelevant.

The insight: The problem isn't paper vs digital cards. It's the entire networking workflow.

Traditional flow: 1. Arrive at event blind 2. Random encounters 3. Awkward small talk 4. Exchange cards 5. Cards go in pocket/wallet/trash 6. Never follow up

New flow with Yenhyia: 1. See attendees before event (prep who to meet) 2. Match based on goals (mutual opt-in) 3. Chat starts with context (you both chose each other) 4. Meet in person (not random, intentional) 5. Digital card auto-shared in chat thread 6. Contact synced to phone, conversation history preserved

The technical interesting bits:

- Built matching algorithm that weighs profile similarity, goals, and real-time proximity - Real-time venue mapping so you can find your match in a 5,000 person conference - Privacy-first: location data is ephemeral, deleted post-event - One-tap QR check-in: organizers can deploy without any tech integration

What surprised me:

1. Privacy toggle gets used A LOT. People want to control when they're discoverable. Not everyone wants to network for 8 straight hours at a conference.

2. Pre-event matching has higher engagement than on-site. People actually do their homework before showing up.

3. Event organizers care more about "connections made" metrics than we expected. They want to prove ROI to sponsors and attendees.

Tech stack: React Native, Firebase real-time DB, Node.js, serverless on Google Cloud.

Launched in Ghana/Nigeria because the professional networking ecosystem is still forming here. No legacy LinkedIn graphs, everyone's building from scratch. Perfect test market.

Questions

- How would you approach matching algorithms with sparse initial data? - Best way to handle real-time location at scale (5K+ concurrent users) without destroying battery? - Thoughts on privacy in location-based apps? We delete everything post-event but curious about other approaches.

Code isn't open source yet but considering it for the venue mapping component.

Try it: yenhyia.buzzchat.site

Feedback welcome, especially on the tech and privacy angles.

Show HN: The $1B problem with business cards nobody's solving properly