DataVance
Invoice extraction is only useful if you know when it's wrong — DVAP attaches a 0–1 confidence score to every value it returns.

About DataVance
Most document-AI failures are silent: a total that reads wrong but looks plausible. DVAP is built around that problem. Every extracted field comes back with its own 0–1 confidence score, so your automation posts what it can trust and routes the rest to a human — with reasons attached. Accuracy is measured, not asserted: results on the public SROIE benchmark and a corpus of real invoices are published field by field — 100% on invoice dates, 99% on totals, 0.97 average confidence, 87% of documents passing straight through — and the live table is served by the API itself. The same call validates ABN, GST, and totals arithmetic, screens for fraud and duplicates with named reasons, and matches against a purchase order when you supply one. Median latency is 8.4 seconds per document. Start on the free tier on RapidAPI and judge the numbers before you commit.
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