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What is TinCorrect?

TINCorrect simplifies the IRS TIN matching procedures for 1099 compliance, allowing teams to quickly verify name and TIN combinations before submission, thereby reducing the chance of B-Notices and improving the accuracy of vendor data with minimal manual effort. Users can easily upload combinations of names and TINs or EINs through a spreadsheet, single entry, or API, with the ability to handle batches of up to 100,000 records efficiently. The platform performs validation of each name and TIN combination directly against the IRS TIN Matching Program, providing immediate results in seconds or minutes, in contrast to the lengthy overnight bulk processing usually necessary. It supports common file formats like CSV, Excel, and TSV, manages IRS formatting seamlessly, and automatically eliminates duplicate entries before processing to prevent wasted resources on unnecessary lookups. In addition to delivering essential IRS result codes, TINCorrect also provides detailed explanations and recommended next steps for each record, helping users understand the causes of mismatches, which may include issues like a missing TIN, an invalid TIN, discrepancies in names, incorrect TIN types, duplicate requests, or pending EINs. This extensive functionality not only helps organizations remain compliant but also significantly boosts their operational efficiency, making it an invaluable tool for financial teams. Furthermore, TINCorrect's user-friendly design ensures that even those with minimal technical expertise can navigate the platform effectively.

What is NetOwl NameMatcher?

NetOwl NameMatcher, celebrated for its superior performance in the MITRE Multicultural Name Matching Challenge, offers exceptional accuracy, rapid processing, and scalability in its name matching solutions. Utilizing a cutting-edge machine learning framework, NetOwl adeptly addresses the complex challenges associated with fuzzy name matching. Traditional techniques like Soundex, edit distance, and rule-based systems frequently struggle with precision, leading to an abundance of false positives, and recall issues that result in false negatives, particularly when faced with the varied fuzzy name matching scenarios mentioned earlier. In contrast, NetOwl adopts a data-driven, machine learning-based probabilistic approach to overcome these name matching challenges effectively. It autonomously develops advanced, probabilistic name matching rules from vast real-world datasets containing multi-ethnic name variants. Additionally, NetOwl implements specialized matching models designed for different entity types, including individuals, organizations, and geographical locations. To enhance its functionality, NetOwl incorporates automatic detection of name ethnicity, which significantly boosts its adaptability to the complexities inherent in multicultural name matching. This holistic strategy not only elevates accuracy but also ensures dependable performance across a wide array of applications. Consequently, organizations relying on precise name matching can greatly benefit from the innovative solutions provided by NetOwl.

Media

Media

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
Google Sheets
IBM Cloud
Kibana
MarkLogic
Microsoft Excel
Palantir Apollo
SolrCommerce
Tableau

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
Google Sheets
IBM Cloud
Kibana
MarkLogic
Microsoft Excel
Palantir Apollo
SolrCommerce
Tableau

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

TinCorrect

Company Location

United States

Company Website

tincorrect.com

Company Facts

Organization Name

NetOwl

Date Founded

1996

Company Location

United States

Company Website

www.netowl.com/name-matching-software

Categories and Features

Corporate Tax

Compliance Management
Data Import / Export
Data Verification
Electronic Filing
Exception Notification
For Nonprofits
For Partnerships
K-1 Reporting
Payroll & Employer Forms
Status Tracking
Tax Planning

Categories and Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

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