"Even pay-per-usage is expensive — $5 per 1,000 post-read requests. LLM-level pricing everywhere." Model your real monthly API bill below. Drag the skyline to orbit; every slider rebuilds the towers.
At $5/1k, one user making 40 requests a day costs you 40 × 30 × $0.005 = $6.00/month in data fees alone — before servers, before payroll. If you charge $12, half your revenue is gone at the meter.
Data platforms watched AI companies pay LLM-level rates for tokens and repriced their own APIs to match — social reads, search results, and enrichment endpoints that once cost cents per 10k now cost dollars per 1k.
Sellers justify it as "AI demand"; buyers experience it as a tax on every feature. The practical consequence: per-request cost is now a first-class design constraint, like latency or uptime.
Buy when the data is proprietary (you literally can't get it elsewhere), volumes are low, or speed-to-market beats margin for now.
Build (own pipeline, first-party collection, or a cheaper aggregator) when API spend exceeds roughly one engineer-month per month, when pricing is volatile, or when a vendor's rate hike could kill your unit economics overnight — the calculator above shows exactly where that line is for you.