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features
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support

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Description

DataMatch Enterprise (DME) is Data Ladder's entity resolution and data matching platform. It identifies records that refer to the same person, business, or entity across disconnected systems, then links and consolidates them into a single accurate record. Core functions include data profiling, standardization, matching, deduplication, and merging, supporting use cases such as Customer 360, KYC, fraud detection, and master data management. The platform is available through a no-code visual interface for business users and a REST API for developers, allowing the same matching engine to be embedded in applications, data pipelines, or AI agent workflows. Match results are rule-based and traceable, so users can see the specific logic behind each linked record rather than a single opaque score. Recent additions include entity graphs for visualizing connected records, live search for real-time matching, and Docker as a deployment option in addition to cloud and on-premises environments. Independent benchmarking across 15 studies shows DME identifying 5 to 12% more matches than comparable tools, with fewer false positives and accuracy up to 99%. In a large-scale test, it processed 10 million records in 41 minutes.

Description

Companies that leverage data effectively utilize the Tilores API to establish a cohesive customer profile across all their various source systems. They develop real-time solutions that help mitigate risk, detect fraud, and provide tailored digital experiences, all while avoiding engineering complications. The challenges posed by inconsistent, incomplete, and outdated customer information hinder businesses in their efforts to align, strategize, and report accurately. For organizations to harness their customer data effectively, they must first standardize their schemas and integrate both new and historical data seamlessly. However, even after creating a centralized system with unified customer data, it often necessitates dedicated development efforts to enhance its utility. To streamline this process, it's essential for unified customer data to be synchronized back to the individual source systems of each department, turning every system into a distributed source of truth. This approach empowers businesses to manage risk more efficiently, detect fraud proactively, and enhance customer service. By transforming fragmented and isolated customer data into a comprehensive Customer 360 view, organizations can unlock new insights and drive better decision-making. Ultimately, this unification fosters a deeper understanding of customer behavior, enabling continuous improvement and innovation.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

GraphQL No 
HubSpot CRM No 
HubSpot Customer Platform No 
Salesforce No 
Snowflake No 

Integrations

GraphQL Yes 
HubSpot CRM Yes 
HubSpot Customer Platform Yes 
Salesforce Yes 
Snowflake Yes 

Pricing Details

starts at $10000/user per year
Free Trial Yes 
Free Version No 

Pricing Details

$2000/month
Pricing is based on Unified Customer Records (UCRs), which is the ultimate number of customers you have in Tilores, regardless of the number of data records.
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Data Ladder

Founded

2006

Country

United States

Website

dataladder.com

Vendor Details

Company Name

Tilores

Founded

2021

Country

Germany

Website

tilores.io

Product Features

Data Cleansing

Address/ZIP Code Cleaning Yes 
Charting No 
Data Consolidation / ETL No 
Data Mapping Yes 
Multi Data Format Support Yes 
Phone/Email Validation Yes 
Raw Data Ingestion No 
Sample Testing No 
Validation / Matching / Reconciliation Yes 

Data Quality

Address Validation Yes 
Data Deduplication Yes 
Data Discovery No 
Data Profililng Yes 
Master Data Management No 
Match & Merge Yes 
Metadata Management No 

Product Features

Alternatives

Alternatives

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