Processes
What is Data Extraction?
Data extraction is the process of identifying and pulling specific data fields from source documents, databases, or systems — converting raw information into usable, structured data.
Explanation
In accounting automation, data extraction is the first step in any document workflow. Before you can match an invoice to a PO, code it to the GL, or post it to the ERP, you need to extract the relevant fields: vendor name, invoice number, date, line items, totals, payment terms. The quality of extraction directly determines the quality of everything downstream. AI-based data extraction achieves higher accuracy than rules-based approaches because it understands document context and handles layout variation. Extraction quality is typically measured by field accuracy rate — the percentage of fields correctly extracted across a document set.
How Rima relates
Rima extracts data from any accounting document type — invoices, bank statements, receipts, financial reports — with 99%+ accuracy and a complete audit trail.
Explore data extractionRelated Terms
OCR (Optical Character Recognition)
Technology that converts scanned documents and images into machine-readable text.
Structured Data Extraction
The process of pulling specific, organized fields from unstructured documents like PDFs or emails.
AI Document Processing
Using artificial intelligence to automatically extract, classify, and process data from documents.
Data Mapping
Defining how data fields from a source document correspond to fields in a destination system.
See it in action
Rima automates the manual document workflows accounting teams spend hours on every week.