Methodology & data.

How a row is built

One row is a product × plan × capture date. A product qualifies when its public pricing page carries a numeric, depletable meter — credits, tokens, tasks, actions, outcomes. Because a credit means something different everywhere, the Index works in three comparable layers and never compares raw $/credit across products:

• Unit-free within-product ratios — top-up premium over a plan’s own bundle, tier-to-tier discount curves. The unit cancels.
• Policy distributions — rollover, expiry, behaviour at zero, seat scaling. Counted across the panel.
• Task-equivalent prices within a category — only where the credit-to-action mapping is public, and only where the task is the same.

Sources are vendors’ own public pricing pages and help docs only — never third-party trackers, leaks, or estimates (those may annotate a row, never populate it). Every published row is pinned to at least one Wayback Machine snapshot. Promos and regional prices are flagged and excluded from metrics. Prices visible only behind the logged-in purchase screen are recorded as in-app only and kept out of public aggregates — the opacity is reported, not imputed. Derived figures are computed at build; none is hand-entered, and missing is missing — no imputation, ever.

What we excluded — and why

The inclusion test is deliberately strict, and plenty of well-known AI software fails it. The reasons are part of the picture — not every AI product meters, and where the meter is absent is itself a finding:

• Flat per-seat AI, no meter — e.g. Granola (AI meeting notes; $14–$35/user, “unlimited”). Priced like classic SaaS — nothing to meter.
• Caps without purchasable units — e.g. Wispr Flow (AI dictation; 2,000 words/week free, then a flat “unlimited” Pro at $15). A cap, but you upgrade rather than buy more, so there’s no top-up economics to read.
• No first-party AI product — e.g. Obsidian (a notes app; AI is third-party plugins). Out of scope.
• Raw API token pricing (OpenAI / Anthropic / Google per-token rates) — a different layer; this study is about the abstraction products wrap around tokens.
• Negotiated enterprise pricing — unobservable; tracked instead on the opacity watchlist.
• Promos, regional, and lifetime prices — flagged and kept out of the metrics so the quarterly time series stays clean.

The panel & source ledger

Every published product, its computed bundled-rate range, whether the top-up price is public, and the dated source + archive each row rests on. The full per-plan dataset is the /benchmarks/credit-index.json endpoint (published observations only).

The Index is published under CC BY 4.0: free to reuse — including by AI engines — with attribution to Strategy of Finance — The AI Credit Index.

† Borderline inclusion — sits near the raw-API exclusion line; captured anyway, flagged here.