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Data reconciliation software for audit and accounting teams. Describe the test and approve the plan, and Data Match checks each item against its source document, with cited evidence behind every result.
Whether it’s tests of details or vouching, matching samples to source PDFs takes hours every week. In Trullion’s survey, 59% of auditors spend more than five hours a week on manual PDF extraction, and nearly half name reconciliations as their top challenge.
Data Match reads the supporting documents and checks each item in your sample against them, so you spend less time looking things up one at a time.
Each result is saved with its source: the value, the document and the page. A reviewer can reperform the match without asking the preparer.
Data Match flags mismatches and missing support, so you review the exceptions instead of every row.
Data Match is data reconciliation software that runs inside the procedure you approve, so the test follows your plan and the results come back with their evidence. Work directly with Trulli to orchestrate your plan.
Data Match supports the reconciliation and vouching work wherever it happens
Vouch and trace samples to source documents during fieldwork, then carry the results into your Financial Statement Validation review.
Run test-of-details and vouching procedures with documented evidence behind every result, as part of Substantive Testing.
Reconcile internal financial data to supporting documents before reporting, and keep the support with each result.
Workflow time reduced by
Reed Chase
Partner and Assurance Practice Leader, Tanner
Faster financial close
Dionn DuBois
Corporate Accounting Manager, Virgin Voyages
Pull structured data, linked to the source
Tie out with exceptions flagged
Let Trulli coordinate tools and agents
Faster matching only helps if the work holds up in review. Data Match returns every result with its source, so a reviewer can reperform the match.
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 reduces manual matching work and keeps the source with every result. Data Match works on its own or inside Trulli, Trullion’s orchestration layer.
Data Match automates core parts of substantive testing, such as vouching transactions to source documents and tracing data back to original records. It flags matches and discrepancies, and each result links to its source.
Yes. Data Match produces structured reports with clear match results, exception details, and links to source documents. Teams can use them to support their testing conclusions and reduce the manual work of 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.
Data reconciliation software compares data from two sources and flags where they disagree. In audit and accounting, that usually means checking figures in a workpaper, ledger or sample against source documents such as invoices, contracts and bank statements. Data Match is data reconciliation software built for that work, and it keeps the evidence with each result so a reviewer can check it.
AI can do much of the finding and comparing: reading documents, extracting values and matching them to your data. People still decide what to test and what the results mean. With Data Match you approve the plan before it runs and review flagged exceptions against the source.
Account reconciliation software typically matches transactions between ledgers, bank accounts or subledgers during the close. Data Match reconciles financial data against source documents, which is the vouching and tracing work auditors and accountants do to support a balance or a test of details.