Startup Billing: Models, Build vs Buy, and What to Enforce

Startup billing converts subscriptions and product usage into invoices, payments, revenue reporting, and related processes such as metering, rating, dunning, tax, and reconciliation. The text argues that AI products complicate traditional per-seat pricing because tokens, API calls, agent actions, and compute create variable costs, making usage-based, credit-based, or hybrid models more suitable when costs closely follow consumption. Billing infrastructure should generally evolve with a company’s stage, beginning with simple checkout and subscriptions, then adding product catalogs, entitlements, proration, payment recovery, quote-to-cash workflows, and real-time usage controls as pricing and customer needs become more complex. It distinguishes billing, which records consumption and determines charges after use, from enforcement, which uses entitlements, credits, and limits to approve or block requests before additional costs occur. The text recommends evaluating systems based on reliable metering, duplicate-event handling, configurable pricing, dunning, financial auditability, developer tooling, data portability, and support for credits and request-time limits, while warning that failed payments, inaccurate proration, unmetered usage, and uncontrolled overages can cause revenue leakage. It presents Stigg as a complementary runtime layer for AI products that enforces entitlements, credits, and spend limits synchronously without replacing an existing payments or invoicing platform.

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