Everstring
EverString was a B2B predictive marketing and sales intelligence platform that used data science, machine learning, and a proprietary business data cloud to help go-to-market teams identify their best-fit accounts. Its capabilities included predictive lead and account scoring, account-based marketing segmentation, firmographic enrichment, similar-company discovery, ML-generated keywords, and industry classification, exposed to developers through an Enrichment API on developer.everstring.com secured with access-token authentication. Founded in 2012 and backed by investors including Lightspeed Venture Partners, EverString was acquired by ZoomInfo in November 2019 and its data and predictive capabilities were folded into the ZoomInfo platform; the everstring.com website now redirects to ZoomInfo Operations and the standalone developer portal has been largely decommissioned. This profile documents the historical API surface and current public footprint.
Index entry only — little beyond a description and a link, and nothing machine-readable enough for an agent to act on without a human reading the site first.
API Evangelist profiles Everstring the way a machine reads it — 2 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Everstring scores 11.0/100 (minimal), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
How we profile Everstring
Each block below is one kind of artifact we hold for Everstring. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 1
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
EverString Enrichment API
The EverString Enrichment API exposed EverString's data cloud, AI, and machine-learning components as a micro-service - similar-company discovery, ML-generated keywords, industr...
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Everstring — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Company 1
The organization behind the API
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