data engineering apis

Use our Latest AI Models for Best Matching Results with Global Individual Name Data

by Interzoid Team

You can now call our Individual Name Matching API using our "AI-Plus" model with the name of an individual as a parameter for all worldwide data. A call to this Cloud API results in our AI models generating a hashed, canonical key string based on the name of the individual. The key is the same for all variations of the individual name. This key can be used to find similar records in the same dataset (simply sort the data by generated similarity key, like the matched similarity key clusters below). It can also be used to match data across datasets to get much higher match rates, such as in a data augmentation process.

Sample API/URL Query:*****&fullname=John Smith
Sample JSON Output:
You can also set a header value for your API License Key (*recommended for production environments):
Curl Example:
curl --header "x-api-key: fh5hs7*****" " Smith"

Here are some example matching records that in this example have been matched/clustered because they share the same generated similarity key:

Matching individual person names and organization names with AI examples Matching individual person names and organization names with AI examples

Using Interzoid's Cloud-native, AI-powered data quality and data matching capabilities, you can maintain accurate, standardized, and normalized individual name data, unlocking data-accelerated opportunities and driving significant business value from each of your high quality strategic data assets.

Try it out here.

Why is inconsistent name data an issue?

Having inconsistent individual name data present within your important data assets can lead to several problems in data-driven applications, processes and initiatives. Here are some examples.

Duplicate data and untrustworthy business intelligence:

When the same individual is collected and stored under multiple variations of their name, it leads to duplicate records of the same person within organizational data assets. This will skew analytics, reports, and dashboards, leading to incorrect insights and potentially flawed decision-making. For example, if a individual's purchases are split across multiple name variations, the true total sales figure for top customers may be underreported, causing lost opportunities for targeted marketing or resource allocation.

Significant difficulty in data integration and analysis:

Inconsistent naming conventions make it challenging to integrate data from different sources or systems. This can lead to time-consuming manual data cleansing and reconciliation efforts, increasing labor costs and delaying analysis and decision-making processes.

Lost opportunities for Customer Relationship Management (CRM):

When customer data is fragmented due to inconsistent corporate name data, it becomes difficult to gain a comprehensive view of a customer's interactions and history with your organization. This can result in missed opportunities for cross-selling, upselling, or providing personalized services, ultimately impacting customer satisfaction and revenue growth.

Compliance issues:

In some industries, inconsistent individual name data can lead to compliance and regulatory problems. For example, in financial services, failing to accurately identify and aggregate data related to a single person may result in non-compliance with anti-money laundering (AML) or know-your-customer (KYC) regulations, leading to potential fines and reputational damage.

Business process and operational inefficiencies:

Inconsistent individual names can cause operational inefficiencies in various business processes, such as invoicing, contract management, and vendor relations. These issues can lead to increased manual work, errors, and delays, resulting in higher operational costs, vendor overpayments, and potential missed opportunities for early payment discounts or favorable contract terms.

See our Snowflake Native Application. Achieve Data Quality built-in to SQL statements.
Identify inconsistent and duplicate data quickly and easily in data tables and files.
Connect Directly to Cloud SQL Databases and Perform Data Quality Analysis
Achieve better, more consistent, more usable data.
Try our Pay-as-you-Go Option
Start increasing the usability and value of your data for $20 USD!
Launch Our Entire Data Quality Matching System on an AWS EC2 Instance
Deploy to the instance type of your choice in any AWS data center globally. Start analyzing data and identifying matches across many databases and file types in minutes.
Free Usage Credits
Register for an Interzoid API account and receive free usage credits. Improve the value and usability of your strategic data assets now.
Automate API Integration into Cloud Databases
Run live data quality exception and enhancement reports on major Cloud Data Platforms direct from your browser.
Check out our APIs and SDKs
Easily integrate better data everywhere.
Example API Usage Code on Github
Sample Code for invoking APIs on Interzoid in multiple programming languages
Business Case: Cloud APIs and Cloud Databases
See the business case for API-driven data enhancement - directly within your important datasets
Documentation and Overview
See our documentation site.
Product Newsletter
Receive Interzoid product and technology updates.

All content (c) 2019-2024 Interzoid Incorporated. Questions or assistance? Contact

201 Spear Street, Suite 1100, San Francisco, CA 94105-6164

Interested in Data Cleansing Services?
Let us put our Generative AI-enhanced data tools and processes to work for you.

Start Here
Terms of Service
Privacy Policy

Use the Interzoid Cloud Connect Data Platform and Start to Supercharge your Cloud Data now.
Connect to your data and start running data analysis reports in minutes:
API Integration Examples and SDKs:
Documentation and Overview: Docs site
Interzoid Product and Technology Newsletter: Subscribe
Partnership Interest? Inquire