Regulators want to know if your customer, vendor, and employee records are deduplicated, consistent, and traceable. MatchLogic finds the duplicates, documents why each record matched, and gives you an audit trail you can hand over with confidence.
.avif)
.avif)
.avif)
.avif)
.avif)
We needed to prove to regulators that our policyholder records were accurate and free of duplicates. MatchLogic gave us the documentation to back up every match decision.
When the same customer exists three times in your system, GDPR deletion requests miss two of them. When vendor records are duplicated, spend reports show inflated supplier counts. When employee data has unresolved duplicates, benefits enrollment and payroll calculations break. MatchLogic finds every duplicate, documents the match logic, and produces output your compliance team can defend.
A data subject requests deletion under GDPR. Your team removes their record from the CRM. But that same person exists under a misspelled name in your billing system and under a maiden name in your support database. Two out of three records survive the deletion. You have now failed to comply, and you may not even know it until an audit reveals the gap. MatchLogic identifies every instance of that person across every system before the deletion request is processed.
Internal and external auditors expect clean, deduplicated master data. When they pull a sample and find the same vendor appearing under three different IDs, or the same customer counted twice in a revenue report, the finding gets documented. Repeated findings escalate. MatchLogic gives you the ability to run deduplication before the audit cycle and produce documented results showing exactly which records matched, at what confidence level, and which rules triggered the match.
When a patient has two active records, a lab order placed under one MRN does not appear under the other. The ordering physician does not see that the test was already done, so they order it again. The patient gets an unnecessary blood draw, an unnecessary imaging study, or an unnecessary procedure. The organization absorbs the cost. The patient absorbs the inconvenience and the clinical risk of repeated exposure. MatchLogic prevents this by resolving the duplicate records before orders are placed.
Regulations like GDPR and CCPA require organizations to honor data subject requests across every system. If a customer exists as three separate records, a deletion request might only remove one. Incomplete compliance exposes the organization to fines and audit findings. Duplicate records are a direct liability when regulators come looking.
The new ERP connects to downstream systems through APIs and data feeds. Those integrations assume clean, deduplicated master data. When a customer record exists three times in the new system, downstream processes break in unpredictable ways: order management routes to the wrong account, billing sends invoices to outdated addresses, support tickets open against phantom customer profiles. Every integration point becomes a potential failure point when the underlying data has duplicates.
When employee records are duplicated across HR systems, the downstream effects hit benefits enrollment and payroll. An employee appears twice, triggering double enrollment or miscalculated withholdings. The errors compound over pay periods and become audit findings during annual benefits reconciliation. MatchLogic deduplicates employee records across HRIS, payroll, and benefits platforms before these errors cascade.
Most matching tools produce a result and call it done. You get a list of merged records with no explanation of why they merged. When an auditor asks how you determined that Record A and Record B are the same entity, you have no answer.
MatchLogic documents every match decision. For every pair of records that link, you can see which fields were compared, what similarity score each field contributed, which algorithm caught the match, and what threshold triggered the final decision. If a name scored 92% on phonetic similarity, an address scored 87% on token matching, and a phone number was an exact match, that breakdown is recorded and exportable.
You can hand this documentation to an auditor, a regulator, or an internal compliance review. The match logic speaks for itself.
Every record pair includes a documented breakdown of which fields matched, which algorithms were used, and what confidence score triggered the link. Export match reports for internal reviews, external audits, or regulatory submissions.
Match your internal records against sanctions lists, denied party databases, PEP lists, or any external reference file. MatchLogic compares across name variations, abbreviations, and transliterations so flagged entities do not slip through on a spelling difference.
Tighten thresholds for financial records where false positives are costly. Loosen them for marketing databases where coverage matters more. Configure different rules for different datasets within the same project, all without writing code.
Before you match, MatchLogic scans every field for completeness, uniqueness, frequency patterns, and format inconsistencies. You see which fields are reliable for matching and which need cleaning first. Profiling is the foundation of defensible matching.
Watch how MatchLogic finds duplicates, documents every match decision, and exports audit-ready reports. Bring your own regulated dataset and we will run it live.
Book a Demo
When a data subject requests access or deletion,you need to find every record that belongs to that person across every system.MatchLogic identifies all variants of a person's record, includingmisspellings, maiden names, abbreviated names, and records with differentidentifiers, so your compliance team can act on the complete set rather than apartial list.
Yes. Every match result includes the fullbreakdown: which fields were compared, what similarity scores were calculated,which matching algorithms were applied, and what thresholds triggered thematch. This output is exportable as a file that an auditor can reviewindependently.
Built-indeduplication tools in MDM and CRM platforms typically produce a merged resultwithout documenting the reasoning. MatchLogic shows you the complete decisiontrail for every match. You can explain to an auditor exactly why two recordslinked at 89% confidence and what would need to change for that match to berejected. Most built-in tools cannot provide this level of visibility.
Yes. You load your internal dataset and yourexternal reference file (sanctions list, PEP list, denied party database, orany other reference) into the same project. MatchLogic compares across bothsources using fuzzy matching to catch name variations, transliterations, andabbreviations that exact-match screening would miss.
Most teams loadtheir data and get matched, documented results within the first day. MatchLogicdoes not require weeks of model training or consultant-led configuration. Ifyou have an audit coming up next month, you can have deduplicated, documentedoutput ready well before the auditors arrive.
MatchLogic starts at $13,000 per year for asingle desktop license. Server deployments for team access start at $45,000 peryear, and API access for pipeline integration starts at $85,000 per year. Thisis typically 90% less than what organizations pay for comparable capabilitiesfrom Informatica, IBM, or Ataccama.
.svg)
