Interzoid 开发人员简介

Interzoid / interzoid

Interzoid builds, deploys, and offers APIs that are easy to integrate, helps organizations improve the value of their data assets, and also extend their I.T. capabilities. API offerings include data matching, data validation, data enrichment, performance monitoring, financial data, and more.

Address Match

Generates a Similarity Key for fuzzy matching with other similar addresses for increased match rates

Company Matching Advanced

Leverage the power of Generative AI, Large Language Models (LLMs), and Machine Learning, along with specialized algorithms and comprehensive databases, to create a 'Similarity Key' for company names. This key enhances data accuracy by enabling intelligent matching of similar organization names, pinpointing data inconsistencies, boosting match rates, and identifying potential duplicate records.

6.9

401 ms

100%

Compare Full Name Match Score

Leverage the power of Generative AI, Large Language Models (LLMs), and Machine Learning, along with specialized algorithms and comprehensive databases to compare two person names to generate a match score from 0-100 based on how similar the names are.

Currency Rate Converter

This API converts currency amounts from one global currency to another

Full Name Match

Leverage the power of Generative AI, Large Language Models (LLMs), and Machine Learning, along with specialized algorithms and comprehensive databases, to create a 'Similarity Key' for individual person names. This key enhances data accuracy by enabling intelligent matching of similar individual names, pinpointing data inconsistencies, boosting match rates, and identifying potential duplicate records.

7.8

40 ms

100%

		Title	Created at (Click to sort ascending)
A	1	Hello, It's only at the country/international level based on the parsing of the email address. This helps in cases where you might want to segment email addresses by country or provide information in a certain language.	Mon 6:14 21/3/22
A	1	Hello, The idea is that the algorithm, callable by the API, generates a similarity key that is used to match similar company names. In the above case, they would generate the same similarity key for each of the three above, which will be distinct from similarity keys generated for other company names such as Apple, Verizon, etc.. You can then match on these similarity keys rather than the data itself for a much higher match rate either within or across data sources. To create a match report, you could create a column with a database for the similarity key, and then sort the data by that similarity key. This will cluster/lineup those records that share the same similarity key. We have built some scripts that do this in an automated manner if you would like to discuss, but it's pretty straight-forward to sort by similarity key if you generate one for each record. Does this help? I would be happy to assist further. Note that we also have a Company Match Advanced API on RapidAPI which provides some more flexibility/sensitivity thresholding on generating the similarity keys. - Bob	Sat 4:59 28/11/20
A	2	Here is a sample output response. The JSON response is all strings, and you can ignore "credits". The SimKey is what is algorithmically generated, and is used to match other similar company names. {3 items "SimKey":"edplDLsBWcH9Sa7ZECaJx8KiEl5lvMWAa6ackCA4azs" "Code":"Success" "Credits":"499758310" }	Thu 12:07 4/6/20

Interzoid / interzoid

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