Which AI tools pay for themselves, which seats are wasted, and where the next dollar of spend should move. Spendassay connects every dollar a company spends on AI — seats, API tokens, and infra — to what engineering teams actually ship.
North star: identify 10–15% of AI spend as recoverable within 30 days — neutral across Copilot, Cursor, Claude, and every API vendor.
Three steps from scattered vendor invoices to a defensible AI P&L your finance team can sign.
Read-only connectors pull seat invoices, API token spend, and infra alongside usage telemetry from every AI vendor — Copilot, Cursor, Claude, and the rest. Nothing is written back.
Spendassay normalizes every dollar and every signal into one ledger, attributes spend to teams, and reconciles throughput against its quality tax. One neutral P&L, not five vendor dashboards.
Each finding names the wasted seats, the underused license, or the tool that pays for itself — with the formula, the evidence tier, and the dollars recoverable this quarter.
Four principles that make the audit credible to a CFO, a works council, and a security reviewer alike.
Every AI vendor grades its own homework. Spendassay is the neutral cross-vendor layer — only raw usage and spend facts, never a vendor's value estimate.
Never individual league tables. Productivity renders at team granularity with a minimum cohort size, so it survives works-council and GDPR review.
Every throughput gain renders beside its quality cost — rework, churn, unreviewed merges. An audit that hides the tax is not credible.
Every dollar claim exposes its formula with editable inputs and sensitivity ranges — the only posture that survives a CFO who has read the METR study.
The constraints are the product. They are what let you deploy Spendassay without a six-month review.
We never rank engineers. Productivity is team-level with a minimum cohort size.
We read metadata and spend — never the contents of your repositories or prompts.
Spendassay observes. It never mutates a seat, a license, or a customer system.
Explore the full audit on live demo data — every surface, every finding, every formula.