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Match financial data in minutes, not days, and stay audit-ready with full transparency and accuracy.
Whether it’s test of details or vouching workflows, matching samples to source data in PDFs takes up endless hours. There’s a smarter way.
Trullion’s AI extracts and matches sample data to supporting documents, eliminating manual lookups and enabling scalable validation.
Generate fully traceable reports that provide a clear audit trail, ensuring compliance and transparency.
Identify and resolve discrepancies automatically before they become costly errors.
Trullion’s Data Match uses AI to automate reconciliation by scanning, validating, and matching financial data with exceptional accuracy.
Workflow time reduced by
Reed Chase
Partner and Assurance Practice Leader, Tanner
Faster financial close
Dionn DuBois
Corporate Accounting Manager, Virgin Voyages
Automate your workflow
Streamline audit workflows
Our agentic AI assistant
Data Match is Trullion’s AI-powered data reconciliation tool that automatically scans, validates, and matches financial data against source documents to streamline substantive testing, vouching, and tracing workflows. It replaces manual matching tasks with scalable, audit-ready automation.
Data Match automates the core parts of substantive testing such as vouching transactions to source documents and tracing data back to original records. Quickly identify matches and discrepancies with full traceability.
Yes. Data Match produces structured reports with clear match results, exception details, and full traceability to source documents. Teams can support their testing conclusions and meet documentation requirements without manually assembling workpapers.
Absolutely. Audit firms use it for fieldwork, vouching, and substantive tests, while corporate accounting teams use it for reconciliation and validation of internal financial data prior to reporting.
Manual matching introduces compounding risks as audit complexity grows: human error from comparing records by hand, limited coverage from sample-based testing, and inconsistent documentation that’s harder to defend during reviews or inspections.
Automated tools like Data Match address these risks by processing full data sets with consistent matching logic and generating traceable outputs for every result.