# Accounting In Accounting, there is a significant volume of paper documents that need to be processed and stored, including invoices, delivery notes, and receipts. \ However, not all suppliers have adopted digital processes, which results in a high volume of paper that needs to be scanned, checked, and imported into systems such as DATEV or SAP in a structured manner. This manual process is time-consuming and can take up to 5 minutes per page. SmartICR offers a solution to this issue by providing a layer to scanned documents that enables them to be stored as searchable and editable PDF-A files. With SmartICR, users can search for specific documents, mark and copy text, and extract important data automatically, eliminating the need for manual data entry and reducing the risk of typos. ### Use-Case 1: Searchable Document Archive Imagine trying to locate an invoice from years ago, but not being able to search for it as the invoices are stored as scanned images without searchable text. With SmartICR, users can search for invoices using keywords and retrieve the necessary information, such as the supplier’s name, quickly and easily. ### Use-Case 2: Automated Invoice Data Extraction SmartICR eliminates the need for manual data entry by automatically extracting important information from invoices, such as the receiver’s name and address, sender’s name and address, invoice date and number, sender’s IBAN and BIC, and sender’s tax ID. This streamlines the accounting process and reduces the risk of typos, saving users time and increasing efficiency. ### Use-Case 3: Automated Receipt Data Extraction SmartICR also offers automated receipt data extraction, providing users with the same important information as invoices, such as the receiver’s name and address, sender’s name and address, receipt date and number, sender’s IBAN and BIC, and sender’s tax ID. This eliminates the need for manual data entry, reducing the risk of typos, and increasing efficiency. ### Conclusion In conclusion, smartICR is a valuable tool for accounting departments, as it streamlines the process of scanning, archiving, and extracting data from paper-based documentation, saving time and effort and reducing the risk of errors. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.laigo.ai/use-cases/accounting.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.