ReposiTrak Announces Patent-Pending Touchless Error Correction Technology for Automated Error Detection and Correction of Traceability Data
ReposiTrak Announces Patent-Pending Touchless Error Correction Technology for Automated Error Detection and Correction of Traceability Data
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editechnical
EDI (electronic data interchange) is a standardized computer-to-computer way for businesses to send and receive routine documents—such as invoices, purchase orders, and shipment notices—directly between systems without paper or manual retyping. Like a well-run conveyor belt, EDI reduces errors, speeds processing and payments, and increases visibility into the supply chain, so changes in EDI use or failures can materially affect a company’s costs, cash flow and operational reliability.
csvtechnical
A CSV (comma-separated values) file is a simple text format that stores table-like data, with each line as a row and commas (or other delimiters) separating columns. Investors use CSVs to move price histories, financial statements or transaction records between programs because they are lightweight, widely readable and easy to import into spreadsheets or analysis tools — like a printed spreadsheet saved as plain text — which helps with quick analysis, record-keeping and auditing. Be mindful that mis-placed commas or different date formats can cause errors when importing data.
xlsxtechnical
An .xlsx file is the common spreadsheet file format used by Microsoft Excel and compatible programs to store tables of numbers, formulas, charts and text. For investors it matters because these files often hold financial models, earnings schedules, and raw data that drive valuation and decision-making — like a digital ledger or workbook that lets analysts sort, calculate and visualize results quickly and share them with others.
xmltechnical
XML is a plain-text format that labels and organizes data so both computers and people can read and process it, like putting information into clearly marked folders. Investors benefit because financial filings, news feeds, and market data delivered in XML can be automatically pulled, compared and analyzed by software, speeding up research and reducing manual errors. When companies and regulators use XML, it makes tracking changes and integrating data into models and portfolios much easier.
jsontechnical
JSON is a lightweight text format for organizing and exchanging data, using simple name/value pairs much like labeled boxes that hold specific pieces of information. It matters to investors because most market data feeds, trading platforms and financial apps use JSON to deliver prices, news and company disclosures quickly and consistently, so reliable JSON feeds help ensure timely, accurate information for decisions and automated systems.
apitechnical
An API, or Application Programming Interface, is a set of rules that allows different software programs to communicate and work together smoothly, much like a waiter translating your order into the kitchen and then bringing your meal back. For investors, APIs are important because they enable real-time access to financial data, trading systems, and other digital services, making it easier to make informed decisions quickly and efficiently.
canonical data modeltechnical
A canonical data model is a unified, agreed-upon format for representing information so different computer systems can share and understand the same data without repeated tweaking. Think of it as a common language or standard plug adapter that lets varied systems communicate cleanly; for investors, it matters because it lowers integration costs, speeds product and reporting rollouts, reduces data errors, and makes company IT operations more reliable and scalable.
audit trailtechnical
A chronological record that shows who performed each action, when it happened, and what was changed across financial systems and documents; it logs transactions, edits, approvals, and access so every step can be traced. For investors, an audit trail matters because it boosts trust and accountability—helping detect errors or fraud, supporting audits and regulatory checks, and making financial reporting and due diligence clearer, like a transaction-level receipt for a company’s records.
Breakthrough technology advancement solves the biggest problem in traceability -- an unacceptably high error rate -- ensuring the quality and accuracy of data
SALT LAKE CITY--(BUSINESS WIRE)--
ReposiTrak (NYSE: TRAK), the world’s largest food traceability and regulatory compliance network, today announced its patent-pending system and methods for automated error detection and context-aware correction of food traceability data, to address average data error rates of 40% in all traceability records.
The patent-pending technology addresses a critical industry problem: traceability and transactional files that technically conform to standards but contain content errors such as missing or incorrect lot codes, inaccurate product identifiers, and inconsistent shipping details—issues that typically require costly and time-consuming manual correction.
ReposiTrak’s patent-pending system ingests heterogeneous data formats, including EDI, CSV, XLSX, XML, JSON, and API feeds, and normalizes them into a canonical data model. A hybrid engine combining deterministic expert rules and AI-driven inference identifies structural, semantic, and contextual anomalies. The system then generates, ranks, and applies candidate corrections using historical records and cross-document correlation, with confidence scoring to determine whether corrections are applied automatically or routed for human review. All actions are recorded with a complete audit trail to support regulatory compliance.
“This patent-pending technology reflects years of hands-on experience operating traceability networks at scale,” said Randy Fields, Chairman & CEO of ReposiTrak. “Other systems don’t even see these errors, knowing how to find them requires the kind of detection mechanism we’ve built from the ground up. By automating both error detection and correction, we reduce manual effort while improving the accuracy, completeness, and auditability of traceability data across the supply chain. Without an error detection/correction method, data shared via EDI or other common protocols will be riddled with errors, making them unreliable for traceability.”
The patent-pending invention supports supplier-specific behavioral models, configurable confidence thresholds, continuous learning from human adjudication, and explainable correction logic, reliable, touchless traceability with dirty data in and clean data out.
About ReposiTrak
ReposiTrak (NYSE:TRAK) provides retailers, distributors, suppliers, food manufacturers, and wholesalers with an integrated suite of solutions to reduce risk, maintain regulatory compliance, strengthen operational controls, and increase sales through enhanced brand protection. ReposiTrak’s cloud-based platform spans three product families—food traceability, compliance and risk management, and supply chain solutions—and is supported by an unparalleled team of industry experts. For more information, visit repositrak.com.
