The only viable API charged $0.02 per call. Populating menus for all restaurants just once would cost $16,000—before any customer could meaningfully use the product.
"Can we design an end-to-end system—data collection, search, and API—that delivers national-scale menu data at a price point early-stage products can actually use?"
800K+ restaurants, 60M+ items without collapsing under costs
Continuously detect new restaurants and update menus
Fast enough to power real user-facing applications
Avoid pricing that makes it unsustainable
Instead of paying per request, I built a system that could scrape, normalize, and serve menu data at national scale.
Design and implement scalable, high-performance APIs over large datasets
Build distributed data collection systems that balance freshness and cost
Integrate monetization and access control directly into technical architecture
Make pragmatic tradeoffs between speed, cost, and reliability
Optimize refresh cycles based on actual usage and customer value, not theoretical maximums.
Continuously explore alternative cloud options to keep infrastructure costs in check.
Move beyond self-serve subscriptions into enterprise licensing and integrations.