Interzoid Get Full Name Match Similarity Key API

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

★ Only Publicly Available OpenAPI DocumentData EnrichmentData TransformationapiKey1 EndpointsREST

For Agents

Connect the Interzoid Get Full Name 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 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 Match Similarity Key API API.

Generate a deterministic similarity key for a full-name string in a single field

Collapse contact records that store the same person under different spellings or word orders

Join two contact lists by hashing the full-name column to a similarity key first

Cluster engagement events by person despite typos in the captured name

GET STARTED

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

Explore with Jentic

View OpenAPI Document

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

The Interzoid Get Full Name Match Similarity Key API returns an algorithmic similarity key for a person's full name held in a single field. Variants such as 'John A. Smith', 'Smith, John', and 'Jon Smith' typically produce the same key, so deduplication and contact-merging jobs can join on the key instead of brittle string-equality logic. The single GET /getfullnamematch endpoint authenticates with a license key passed as a query parameter and returns the similarity key as JSON. Use the Full Name Parsed Similarity Key API for first and last name data held in separate fields.

Use Cases

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

★ Contact-table deduplication

CRM admins call the Interzoid Get Full Name Match Similarity Key API for every contact's full-name field and group records that return the same key. Variants like 'John Smith', 'Smith, John', and 'J. Smith' collapse into one cluster so reps no longer call the same person twice from duplicate contact rows.

Iterate the contacts table, call /getfullnamematch with fullname set to each row's name, and group rows by the returned similarity key.

Lead-list cross-reference for B2B contacts

Marketing imports a third-party B2B list and joins it against the existing CRM by computing the Interzoid full-name similarity key on both sides. The similarity-key join captures matches that exact-string compare misses, suppressing duplicate outreach to people already in the database.

Compute /getfullnamematch keys for the name column in the inbound lead list and the existing CRM, then suppress leads whose key already exists in CRM.

Engagement attribution across spellings

Event tracking systems often capture the same person under slightly different name spellings across sessions. Storing the Interzoid full-name similarity key alongside each event lets attribution roll up engagement to a single person, producing accurate per-contact funnel metrics.

On every event ingest, call /getfullnamematch with the captured fullname and store the key as person_match_key for downstream aggregation.

AI agent contact list cleanup

An AI agent assisting with a contact-list cleanup discovers the Interzoid Get Full Name Match Similarity Key API through Jentic and uses it to flag near-duplicate contacts during the sweep. Jentic stores the Interzoid license key in the credential vault and injects it as the license query parameter at execution time, so the agent never sees the raw key.

Search Jentic for 'similarity key for full name', load the Interzoid Get Full Name Match operation, and execute it for each contact's full name, then surface clusters of more than one contact sharing a key.

Key Endpoints

1 endpoints — the interzoid get full name match similarity key api returns an algorithmic similarity key for a person's full name held in a single field.

METHOD

PATH

DESCRIPTION

GET

/getfullnamematch

Return a similarity key for a single-field full name

GET

/getfullnamematch

Return a similarity key for a single-field full name

Why though Jentic?

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

Credential isolation

The Interzoid license key is stored encrypted in the Jentic vault and injected as the license query parameter on each call to /getfullnamematch, so the raw key never enters the agent's context.

Intent-based discovery

Agents search Jentic with intents like 'similarity key for full name'. Jentic returns the Interzoid Get Full Name Match operation with its parameter schema for direct execution.

Time to first call

Direct Interzoid integration: 1-2 hours including license registration and HTTP wiring. Through Jentic: a few minutes via search, load, and execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Interzoid Get Full Name Parsed Match Similarity Key API

Same similarity-key approach but accepts first and last name in separate fields

Choose this when your dataset already splits first and last name into separate columns.

Complementary

Interzoid Get Company Name Match Similarity Key API

Same similarity-key approach applied to company names; pair with full name for B2B contact dedup

Use alongside the full-name match API when both contact name and company need fuzzy matching in the same dedup pass.

Complementary

Interzoid Get Address Match Similarity Key API

Generates a similarity key for a full street address, useful as a tie-breaker for ambiguous name matches

Use as a tie-breaker when full-name keys collide and address is also captured.

FAQs

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

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

The API uses a license key passed as the license query parameter on every call to /getfullnamematch. Through Jentic the license key is held in the credential vault and injected at execution time, so the agent never handles the raw key.

What if my data has first and last name in separate fields?

Use the Interzoid Get Full Name Parsed Match Similarity Key API instead — it accepts firstname and lastname as separate parameters. The /getfullnamematch endpoint expects the full name combined into a single string.

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

The OpenAPI spec does not publish a numeric rate limit. Interzoid enforces per-license-tier quotas on the account dashboard, so check your account before running batch dedup jobs.

How do I deduplicate names through Jentic?

Install the SDK with pip install jentic, search for 'similarity key for full name', load the Interzoid Get Full Name Match operation, and execute it for each name string, then group rows by the returned key.

Does the API handle 'Last, First' formatting?

Yes. The similarity algorithm tolerates common reorderings, so 'John Smith' and 'Smith, John' typically produce the same key. Records with extreme transliteration differences may still need pre-normalization.