Install Jentic One Beta

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.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Finterzoid.com%2Finterzoid-get-full-name-parsed-match-similarity-key-api" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Finterzoid.com%2Finterzoid-get-full-name-parsed-match-similarity-key-api" | 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.

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

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Use Cases

Patterns agents use Interzoid Get Full Name Parsed Match Similarity Key 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 Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the Interzoid Get Full Name Parsed Match Similarity Key API by hand means obtaining a license key, appending it as a license query parameter on each call to /getfullnameparsedmatch, and handling the request plumbing yourself. Through Jentic you install once, import this API from the API Directory, store the license key once, and your agent calls it.

Permission scoping

This API exposes a single read-only GET /getfullnameparsedmatch operation that takes parsed first and last name fields in the query, with no resource id in the URL path, so scoping is at the operation level: you limit the agent to the parsed-name similarity-key lookup it needs. It only computes a match key and writes nothing, so there is no destructive operation to include.

Credential isolation

Your Interzoid license key is stored once, encrypted, by your own Jentic One instance and injected as the license parameter at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'generate a parsed name similarity key', and Jentic returns the Get Full Name Parsed Match operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Interzoid Get Full Name Parsed Match Similarity Key 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 with Jentic One, the self-hosted execution layer.

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.

Can I limit what my agent is allowed to do with the Interzoid Get Full Name Parsed Match Similarity Key API?

Yes. Because Jentic One is self-hosted, your own rules decide which operations and credentials the agent may use, and this API exposes only a single read-only GET /getfullnameparsedmatch operation, so you can scope the agent to just the parsed first-and-last-name similarity-key lookup it needs. That operation only computes a match key from the firstname and lastname query parameters and writes nothing back, so there is no destructive action to grant. The Interzoid license key is stored once by your instance and injected at execution time, so the agent can call the endpoint without ever seeing the raw key.

Interzoid Get Full Name Parsed Match Similarity Key API

Name: Interzoid Get Full Name Parsed Match Similarity Key API
Brand: Interzoid Get Full Name Parsed Match Similarity Key API
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For Agents

Generate a phonetic similarity key for a parsed first name and last name so an agent can match, deduplicate, or merge person records held in two separate name fields.

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 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.

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