Interzoid Get Full Name Parsed Match Similarity Key API

Name: Interzoid Get Full Name Parsed Match Similarity Key API API
Brand: Interzoid Get Full Name Parsed Match Similarity Key API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentData EnrichmentData TransformationapiKey1 EndpointsREST

For Agents

Connect the Interzoid Get Full Name Parsed Match Similarity Key API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Interzoid Get Full Name Parsed Match Similarity Key API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Interzoid Get Full Name Parsed Match Similarity Key API API.

Generate a similarity key from a first name and last name pair to match contact records that differ in spelling or formatting

Group customer rows that share the same parsed-name similarity key for deduplication before a CRM import

Build a join key for cross-database merges where person records use separate first and last name columns

Reduce false negatives in fuzzy contact lookups by comparing similarity keys instead of raw name strings

GET STARTED

Start building with Interzoid Get Full Name Parsed Match Similarity Key API API

Explore with Jentic

View OpenAPI Document

Use for: I need to deduplicate a customer list where first and last names are in separate columns, Generate a similarity key for the contact 'Robert' 'Smith', Find all CRM rows that match the same person despite spelling variations in first and last name, Check whether two contact records refer to the same person using parsed name fields

Not supported: Does not handle address validation, company-name matching, or names stored in a single combined field — use for parsed first-and-last-name similarity key generation only.

Jentic publishes the only available OpenAPI document for Interzoid Get Full Name Parsed Match Similarity Key API, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for Interzoid Get Full Name Parsed Match Similarity Key API, keeping it validated and agent-ready. The API generates a phonetic similarity key from a person's first name and last name when those fields are stored separately, so records that look textually different but represent the same person can be grouped, deduplicated, or merged. It is intended for cleaning customer master data, CRM contact lists, and marketing rosters where common variations such as nicknames, transposed initials, and spelling drift produce false negatives on exact-match joins. The single GET endpoint returns a similarity key string that downstream code can use as a join key in any database or data pipeline.

Use Cases

Patterns agents use Interzoid Get Full Name Parsed Match Similarity Key API API for, with concrete tasks.

★ CRM Contact Deduplication

Reconcile duplicate contact rows in a CRM where the same person appears with minor spelling differences in their first or last name. The Get Full Name Parsed Match Similarity Key API generates a stable key from each firstname and lastname pair so rows that share the same key can be merged in a single pass. The endpoint accepts one record at a time, so agents typically iterate over a contact list and store the returned Simkey alongside each row.

Call /getfullnameparsedmatch with firstname=Robert and lastname=Smith, then again with firstname=Bob and lastname=Smith, and report whether the returned Simkey values match.

Pre-Import Data Cleansing

Generate similarity keys for an inbound contact file before loading it into a data warehouse, so duplicate records are identified at ingest rather than after they pollute downstream analytics. The API turns each parsed name pair into a comparable key that can be indexed in a staging table. Throughput is bound by per-call rate limits and the credits attached to the license key.

For each row in a 500-record contact CSV with FirstName and LastName columns, call /getfullnameparsedmatch and write the returned Simkey to a new SimilarityKey column.

Cross-System Person Match

Identify the same person across two source systems that hold first and last names in separate fields, such as a marketing platform and a billing platform. By generating the Interzoid similarity key for each side and joining on that key, an agent can produce a unified customer view without relying on exact-match strings. This is especially useful when one side stores formal names and the other stores nicknames or initials.

Generate Simkey values for every contact in System A and System B using /getfullnameparsedmatch, then join the two tables on the Simkey column and output the matched pairs.

Agent-Driven Data Quality Workflow via Jentic

An AI agent embedded in a data quality workflow uses Jentic to discover and call the Interzoid Get Full Name Parsed Match Similarity Key API on demand, without hardcoded SDK setup. The agent receives a row, requests a similarity key, and writes the result back to the warehouse. Through Jentic the API key is held in the credential vault and never enters the agent context.

Use Jentic to search for 'generate parsed name similarity key', load the /getfullnameparsedmatch operation, and execute it for the 20 contact rows flagged as potential duplicates.

Key Endpoints

1 endpoints — jentic publishes the only available openapi specification for interzoid get full name parsed match similarity key api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/getfullnameparsedmatch

Generate a similarity key from a parsed firstname and lastname pair

GET

/getfullnameparsedmatch

Generate a similarity key from a parsed firstname and lastname pair

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The Interzoid license API key is stored encrypted in the Jentic vault. Agents receive scoped access at execution time and the raw license value never enters the agent context or logs.

Intent-based discovery

Agents search Jentic with a natural-language intent such as 'generate parsed name similarity key' and receive the /getfullnameparsedmatch operation with its input schema, ready to execute.

Time to first call

Direct integration with Interzoid: roughly half a day to wire up auth, error handling, and credit tracking. Through Jentic: under 15 minutes — search, load, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Interzoid Get Full Name Match Similarity Key API

Same similarity key concept for full names stored in a single combined field rather than parsed first and last name fields.

Choose this when the source data has a single Name column rather than separate firstname and lastname columns.

Complementary

Interzoid Get Company Name Match Similarity Key API

Generates similarity keys for company names, useful alongside person-name keys when deduplicating B2B contact records.

Use together with the parsed name endpoint when reconciling B2B contacts that need both person and company match keys.

Complementary

Interzoid Get Address Match Similarity Key API

Generates similarity keys for postal addresses, often used as a second match key alongside parsed names for household-level dedupe.

Use when name-only matching produces too many collisions and address must be added as a second key.

FAQs

Specific to using Interzoid Get Full Name Parsed Match Similarity Key API API through Jentic.

Why is there no official OpenAPI spec for Interzoid Get Full Name Parsed Match Similarity Key API?

Interzoid does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Interzoid Get Full Name Parsed Match Similarity Key API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Interzoid Get Full Name Parsed Match Similarity Key API use?

The API uses an Interzoid license key passed as the required `license` query parameter on /getfullnameparsedmatch. Through Jentic the license key is held in the credential vault and injected at execution time, so the raw key never enters the agent context.

Can I match records where the first name and last name are in the same field with this API?

No. This endpoint expects firstname and lastname as separate query parameters. For names stored in a single combined field, use the Interzoid Full Name Match Similarity Key API instead.

What are the rate limits for the Interzoid Get Full Name Parsed Match Similarity Key API?

The OpenAPI spec does not declare a numeric rate limit. Each successful call decrements a credit balance returned in the Credits response field, and a 402 status is returned when credits are exhausted. Refer to interzoid.com for current per-license-tier throughput.

How do I generate a similarity key for a parsed name through Jentic?

Install the SDK with `pip install jentic`, then search for 'generate parsed name similarity key', load the /getfullnameparsedmatch operation, and execute it with firstname and lastname values. The returned Simkey field is the value to store as a match key.

What does the API return on success?

A 200 response includes Simkey (the similarity key), Code (status code), and Credits (remaining credit balance). Agents typically persist Simkey alongside each contact row and use it for subsequent equality joins.