Vink

Enables extraction of structured data from messy text with multi-model verification and human-in-the-loop review, surfacing only high-confidence results or flagging uncertain fields for confirmation.

Enables accounts payable teams to extract invoice data from PDFs and images, detect duplicates, normalize vendor names, calculate payment terms, and validate invoice completeness. Supports local extraction for text PDFs and optional vision providers for scanned documents.

Enables accounts-payable teams to turn emailed or uploaded invoice PDFs into structured, source-cited fields via Claude, run deterministic arithmetic, date, PO and duplicate checks, and route each invoice to a named human for approval or rejection through scoped bearer tokens. Also supports listing pending approvals and forecasting what falls due in the coming weeks, with per-extraction cost tracking.

Enables AI coding agents to inspect digital or scanned PDF forms and worksheets, map detected answer slots through a virtual Excel/Set-of-Marks view, and inject baseline-snapped text, multi-line answers, or option marks into clean output PDFs. Supports visual verification of completed pages.