What 1,000 Invoices a Month Really Cost: Five Document-AI APIs
A side-by-side look at AWS, Google, Azure, LlamaParse and Veryfi pricing pages reveals hidden minimums and failed-attempt billing behind the real cost of 1,000 invoices a month.
Document-extraction API pricing pages are built to win a different comparison than the one engineers actually need: per-page rates obscure monthly minimums, and credit systems obscure per-document math. This piece runs the numbers for one concrete workload - 1,000 single-page invoices a month - across five vendors' published July 2026 pricing: AWS Textract, Google Document AI, Azure Document Intelligence, LlamaParse, and Veryfi.
The hyperscalers look identical at $0.01/page, but every attempt is billed regardless of success, and all pipeline work - retries, schema validation, normalization, handling new invoice layouts - falls on the engineering team. Veryfi's per-document rate looks competitive until its $500/month minimum (covering up to 5,000 docs) kicks in, pushing the effective cost per invoice to $0.50 instead of the advertised $0.16.
The author also includes their own product, Kynth Core, in the comparison, offering reproducibility instead of neutrality: an MIT-licensed, open-source accuracy benchmark that anyone can re-run with their own API keys.
The real takeaway for engineers: a per-page rate alone tells you nothing. Without answering what a failed extraction costs, what a minimum commitment actually forces you to pay for, and who owns the surrounding pipeline, no pricing page reflects the true cost of the workload.
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