Data Matching Software for Accurate Cross-System Record Matching
Match records across CRM, ERP, SQL databases, spreadsheets, and legacy systems with an all-in-one data match platform. Exact, fuzzy, and AI-powered data matching helps teams link similar and identical records at scale.
Built for Record Matching & Deduplication at Scale
WinPure helps data teams find and connect records that belong to the same entity, even when information is spread across multiple systems. Using a configurable, no code rule builder, users can define custom match rules, adjust confidence thresholds, and review potential matches before they are consolidated. All decisions are logged & verifiable.
WinPure combines traditional fuzzy matching, AdaptiveMatch™ recommendations, MatchAI™ for entity resolution and Match Graph™ review, so each dataset is matched with the approach that suits it.
Combining Traditional and AI-Assisted Data Matching
WinPure’s data match module is powered by AI data match algorithms that are secure, non-generative and designed to run within your infrastructure. All transformation happens on a copy of your data, which keeps your original data intact. This can support GDPR and HIPAA data compliance requirements.
AI Matching for Entity Resolution
WinPure’s MatchAI™ module reads records holistically rather than comparing them field by field. Where conventional matching fails on transposed names or records with fragmented information, MatchAI™ interprets the full record context to reach a match decision. It runs in your environment, with no external model and no generative AI that can produce hallucinations.
- Entity resolution across tables, with culturally aware name comparison and global address parsing
- Match Explanation™ shows how each entity was formed and why a record belongs to it
- Every match decision is traceable in an audit file
AdaptiveMatch™ for Recommended Methods and Thresholds
AdaptiveMatch™ starts from the match problem and the outcome you want, then aligns each column with a suitable algorithm and threshold based on its data type. Every recommendation arrives pre-filled in the match rule, so you review and refine it before the match runs. Exact, fuzzy, phonetic and numeric columns sit in the same project.
- Recommends a method and threshold for each column from its data type
- Draws on a wider set of matching algorithms, selected by data type
- Every recommendation stays editable before the match runs
Traditional Fuzzy Matching with a Knowledge Base Library
Traditional fuzzy matching compares columns with fuzzy and phonetic algorithms at thresholds you set, which handles the spelling variations, abbreviations and typos found in names, company names and addresses. The Knowledge Base Library adds known variations such as nicknames, titles, street types and company suffixes, and users can save their own custom words for future runs. The more precisely the library is maintained, the higher the confidence scores matching can reach.
- Fuzzy and phonetic algorithms with adjustable thresholds for each column
- Ships with libraries for address parts, company suffixes, titles and contact names
- Applied during comparison only, so your stored data stays unchanged
Turn Duplicate, Fragmented Data into Trusted Master Records
WinPure guides you through every stage of the data matching process, from profiling and preparing your data to identifying duplicate records, creating trusted golden records and exporting clean, reliable data back into your business systems.
Understand Your Data Before You Match
WinPure enables users to review their data quality challenges before matching records. Fields with missing values, inconsistent formats and incomplete information are highlighted with a data quality score that shows the most pressing challenges that needs your attention before the data is matched.
Achieve Key Business Goals with Friction-less Data Matching
Do not let disparate & duplicate data stop you. Cross-match records even without unique identifiers!
CRM & Contact Deduplication
Fragmented records across business, marketing and internal databases distort information. Match and deduplicate contacts to build unified customer views before a migration or consolidation.
Patient Record Matching
Clinical systems often cannot share a common patient identifier. WinPure matches on names, phone numbers and emails across databases and systems.
Cross-Jurisdiction Matching in Governments
Government data spans departments, programmes and years. WinPure matches across sources using name, address and partial identifiers, inside your own infrastructure, with full audit logging.
Data Migration Preparation
Migration projects inherit inconsistency from the source. Matching and deduplicating before go-live means the new platform starts with clean, matched data.
Entity Resolution at Scale
Resolve records that refer to the same real world entity across disconnected sources, so the surviving record becomes a verified golden master that downstream systems can trust.
Mergers & Acquisitions
Combine data from multiple ERPs and CRMs fast, even when record structures, codes and naming conventions differ, with easy comparison, structure mapping and consolidation.
WinPure is the only data matching software that runs entirely on your infrastructure, processes tens of millions of records, and can be setup in seconds.
How WinPure compares with other leading alternatives.
| Feature | WinPure | Other Match Tools | Manual workflows |
|---|---|---|---|
| Localised AI Matching | ✓ MatchAI™ reads full records holistically and resolves transposed fields and cross-field ambiguity | ✗ Not available: algorithms are rule-based only | ✗ Not applicable |
| Automated master record selection | ✓ SmartMaster AI™ scores every matched group on completeness, consistency, and reliability to select the golden record | — Manual survivorship decisions required after matching | ✗ Manual review |
| Built-in data cleaning before matching | ✓ Clean and standardise data within the same platform before match rules run | — Matching only. Some tools have limited data cleaning options | ✗ Separate process. No integration |
| Knowledge Base Library | ✓ Persistent dictionary of value equivalences and known variations that feeds directly into match logic | — Not available as a named capability | ✗ Manual categorisation |
| Fuzzy algorithm selection per field | ✓ Algorithm type is selectable and adjustable per field without rebuilding the project | — Single algorithm applied across the project | ✗ Limited ability to change algorithms per column or field |
| GoldenID™ | ✓ Assigns a persistent identity to every matched entity | ✗ Not available in most DQ platforms | ✗ Not available |
| Audit log for compliance review | ✓ Immutable log of every match decision | — Available in some tools but not a primary feature | ✗ Manual documentation only |
| AdaptiveMatch™ recommendations | ✓ Recommends a method and threshold for each column from its data type, and every recommendation stays editable | — Availability varies by tool. Rules are commonly configured column by column | ✗ Rules built and tuned by hand |
| Entity resolution across tables | ✓ MatchAI™ resolves records into entities across tables and systems, with no shared identifier required | — Availability varies by tool, and is often limited to deduplication rules | ✗ Cross-system comparison done by hand |
| Match Graph™ and Match Explanation™ | ✓ Shows which record pairs matched, by which rule and with which score, and why a record belongs to its entity | — Explainability varies by tool | ✗ Manual review of each pair |
| Scheduled matching runs | ✓ Cleaning, matching and MatchAI™ tasks run on a schedule without opening the application | — Scheduling varies by tool and edition | ✗ Each run started by hand |
The Future of Data Matching
Adaptive, explainable and connected matching: what the four trends mean for data teams and how Clean&Match Enterprise™ v12 applies them.
Rated as the top data matching solution
Independent review platforms and customer feedback from teams using WinPure in production.
What Customers Ask Before Using WinPure’s Data Matching Software
Start a conversation about your data matching project.
Migration deadline, a deduplication project, or a larger entity resolution requirement – we will help you understand what WinPure can deliver and how quickly.