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AI-powered accounting and automated bookkeeping for rapid-growth enterprises.

The Intelligent Automation Platform for Audit and Finance Professionals within Microsoft Excel.

DataSnipper is a market-leading intelligent automation platform that functions as a sophisticated Excel Add-in, revolutionizing the way audit and finance professionals handle unstructured data. Its technical architecture leverages advanced Optical Character Recognition (OCR) and proprietary machine learning models to create a seamless link between Excel cells and source documentation (PDFs, images, or scanned files). In 2026, DataSnipper has solidified its position as the enterprise standard by integrating Generative AI (LLMs) to perform semantic cross-referencing and automated anomaly detection. Unlike standalone IDP platforms, DataSnipper’s 'in-Excel' strategy minimizes friction, allowing users to perform complex reconciliation tasks, internal control testing, and financial statement procedures without leaving their primary workbook environment. The platform provides a robust audit trail through 'Snips'—hyperlinked references that maintain a permanent connection between extracted data and the original evidence, significantly reducing review time and increasing documentation quality for global accounting firms and internal audit departments.
DataSnipper is a market-leading intelligent automation platform that functions as a sophisticated Excel Add-in, revolutionizing the way audit and finance professionals handle unstructured data.
Explore all tools that specialize in bank reconciliation. This domain focus ensures DataSnipper delivers optimized results for this specific requirement.
Automatically reconciles data in an Excel sheet against hundreds of source documents using fuzzy matching algorithms.
A specialized module that automates mathematical accuracy checks, internal consistency, and prior-year comparisons.
Deep-learning based OCR that recognizes table structures in unstructured PDFs and maps them directly to Excel grids.
Identifies recurring fields across multiple documents to extract specific data points into a summary table.
Global search functionality that indexes all imported documents within a workbook for specific keywords or numbers.
Visual markers that remain attached to Excel cells, providing a direct hyperlink to the source page and coordinate.
Utilizes LLMs to identify semantic discrepancies between document content and Excel inputs.
Download the DataSnipper Excel Add-in installer from the official portal.
Execute the .msi or .exe file with administrative privileges for Excel integration.
Launch Microsoft Excel and navigate to the newly visible DataSnipper tab.
Authenticate via Single Sign-On (SSO) or corporate email credentials.
Import source documents into the DataSnipper document viewer sidebar.
Run the 'Document Organizer' to categorize and OCR-process imported files.
Utilize 'Table Snip' to extract structured data from PDF tables into Excel.
Apply 'Document Matching' to cross-reference Excel datasets with imported evidence.
Review 'Snips' to verify accuracy and maintain the hyperlinked audit trail.
Export the finalized workbook with embedded evidence for peer review.
All Set
Ready to go
Verified feedback from other users.
"Users consistently praise DataSnipper for its 'life-changing' impact on audit workflows, specifically noting the reduction in tedious manual data entry. Some users mention a learning curve with complex table layouts, but the overall sentiment is overwhelmingly positive due to the time savings and documentation quality."
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