Evertune

Evertune is a Generative Engine Optimization (GEO) and AI brand-intelligence platform that helps brands, marketers, and agencies understand, measure, and influence how they appear in AI-driven recommendations. As discovery shifts from traditional search engines to conversational answer engines like ChatGPT, Claude, Gemini, and Perplexity, Evertune tracks brand visibility and sentiment across 10+ AI models, analyzes how large language models describe a brand versus its competitors, and delivers prescriptive message and content briefs to improve that positioning. The platform combines large-scale prompt testing (100,000+ prompt responses per report via direct base-model API access), the EverPanel consumer panel, daily consumer-app data, an AI Brand Index and AI Brand Score, content activation, and AI advertising. Founded in 2024 by operators who helped scale The Trade Desk, Evertune is backed by Felicis and serves customers including Roku, WPP, athenahealth, and HexClad. Evertune is a data consumer of the major model APIs; it does not currently publish a first-party developer API, SDK, or OpenAPI.

Evertune is profiled on the APIs.io network. Tagged areas include Company, Generative Engine Optimization, AI Search, Brand Monitoring, and Marketing Intelligence.

Evertune’s developer surface includes documentation, pricing, engineering blog, signup flow, YouTube channel, authentication, and 14 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

29.4/100 thin ▬ flat Agent 5/100 human only Front door AI 6/6 dominant Heartbeat 66/100 alive saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessPaid

0 APIs

Company Generative Engine Optimization AI Search Brand Monitoring Marketing Intelligence AI Visibility Analytics Artificial Intelligence

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 29.4/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 4.9 / 17

Access Clarity 11.2 / 17

Operational Transparency 0.3 / 11

Contract Governance 1.9 / 10

Discoverability 4.7 / 9

Regulatory Posture 4.8 / 15

Agent readiness — 5/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0

11 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 28.6 — up to +14.3 composite points
Operational Transparency scores 2.6 — up to +12.7 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/evertune/apis.yml: open an issue on github.com/api-evangelist/evertune to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Reviews, Ratings and UGC (review platforms and who integrates with them)	undeclared	-	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Evertune API pricing

Prices published by Evertune.

Plan	Price
Pro	$800
Enterprise	—

Plan details, limits and sources →

Pricing Plans 1

Published pricing tiers and plan structures.

Evertune Plans Pricing

2 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Evertune Rate Limits

0 limits

RATE LIMITS

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Evertune Authentication

openIdConnect/oauth2 · 1 scheme

SECURITY

Evertune Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Scopes 1

OAuth scopes governing access to this provider's APIs.

Evertune Scopes

14 scopes · authorizationCode/clientCredentials/implicit

14 scopes

SCOPES

Resources

Get Started 2

Portal, sign-up, and the first successful call

Login

SignUp

SignUp

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

WellKnown

WellKnown

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

OAuthScopes

OAuthScopes

Learn 1

Tutorials, courses, talks, and written guidance

YouTube

YouTube

Operate 2

Status, limits, changes, and where to get help

RateLimits

RateLimits

HelpCenter

HelpCenter

Commercial 4

Pricing, plans, and the legal terms of use

Pricing

TermsOfService

PrivacyPolicy

Plans

Company 3

The organization behind the API

Website

Website

Blog

Blog

LinkedIn

Source (apis.yml)

aid: evertune
name: Evertune
description: Evertune is a Generative Engine Optimization (GEO) and AI brand-intelligence platform that helps brands, marketers,
  and agencies understand, measure, and influence how they appear in AI-driven recommendations. As discovery shifts from traditional
  search engines to conversational answer engines like ChatGPT, Claude, Gemini, and Perplexity, Evertune tracks brand visibility
  and sentiment across 10+ AI models, analyzes how large language models describe a brand versus its competitors, and delivers
  prescriptive message and content briefs to improve that positioning. The platform combines large-scale prompt testing (100,000+
  prompt responses per report via direct base-model API access), the EverPanel consumer panel, daily consumer-app data, an
  AI Brand Index and AI Brand Score, content activation, and AI advertising. Founded in 2024 by operators who helped scale
  The Trade Desk, Evertune is backed by Felicis and serves customers including Roku, WPP, athenahealth, and HexClad. Evertune
  is a data consumer of the major model APIs; it does not currently publish a first-party developer API, SDK, or OpenAPI.
url: https://raw.githubusercontent.com/api-evangelist/evertune/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- felicis
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: paid
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Paid
  confidence: high
  probe_state: none
  source:
  - plans
  - authentication
  - scopes
  - rate-limits
  - security
  generated: '2026-11-06'
  method: derived
image: https://cdn.prod.website-files.com/65fc8aa2e86478511b710078/68b8a3ea1e6fb2d5d5503742_Logo.svg
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-08-13'
tags:
- Company
- Generative Engine Optimization
- AI Search
- Brand Monitoring
- Marketing Intelligence
- AI Visibility
- Analytics
- Artificial Intelligence
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: RateLimits
  url: rate-limits/evertune-rate-limits.yml
- type: Website
  url: https://www.evertune.ai/
- type: Documentation
  url: https://docs.evertune.ai/
- type: HelpCenter
  url: https://docs.evertune.ai/
- type: Pricing
  url: https://www.evertune.ai/pricing
- type: Blog
  url: https://www.evertune.ai/resources/blog
- type: Login
  url: https://auth.evertune.ai/u/login/identifier
- type: SignUp
  url: https://www.evertune.ai/get-started
- type: TermsOfService
  url: https://www.evertune.ai/legal/terms-of-service
- type: PrivacyPolicy
  url: https://www.evertune.ai/legal/privacy-policy
- type: LinkedIn
  url: https://linkedin.com/company/evertune-ai
- type: YouTube
  url: https://www.youtube.com/@evertune-ai/videos
- type: GitHubOrganization
  url: https://github.com/Evertune-AI
- type: LLMsTxt
  url: llms/evertune-llms.txt
- type: DomainSecurity
  url: security/evertune-domain-security.yml
- type: WellKnown
  url: well-known/evertune-well-known.yml
- type: Authentication
  url: authentication/evertune-authentication.yml
- type: OAuthScopes
  url: scopes/evertune-scopes.yml
- type: Conformance
  url: conformance/evertune-conformance.yml
- type: Plans
  url: plans/evertune-plans-pricing.yml
x-enrichment:
  date: '2026-08-13'
  status: minimal
  artifacts_added: 8
  pass: local-v1
x-coverage:
  state: none
  reason: no-developer-program
  detail: 'Evertune is a consumer of the model providers'' APIs rather than a publisher of one — its own FAQ says base-model
    data is "reachable only through direct API integration with the model provider" — and it ships no developer surface of
    its own: the pricing page''s two demo-led tiers name no API access, the Intercom help center holds three end-user articles,
    and app.evertune.ai is a closed SPA whose backend is undocumented; the only machine-readable thing Evertune serves is
    the Auth0 OIDC discovery document on auth.evertune.ai, which signs users in to that app.'
  evidence:
  - url: https://auth.evertune.ai/.well-known/openid-configuration
    status: 200
  - url: https://www.evertune.ai/pricing
    status: 200
  - url: https://docs.evertune.ai/llms.txt
    status: 200
  - url: https://www.evertune.ai/openapi.json
    status: 404
  - url: https://www.evertune.ai/.well-known/agent-card.json
    status: 404
  checked: '2026-08-13'

Evertune API — frequently asked questions

How do I authenticate with the Evertune API?

Evertune uses bearer-token authentication (openIdConnect/oauth2 · 1 scheme). The details are profiled on APIs.io as Evertune Authentication.

How much does the Evertune API cost?

Evertune publishes its prices; its Pro plan is $800 as of 2026-08-13. APIs.io lists 2 pricing plans for Evertune, with each plan's price, limits and inclusions under Pricing on this page.

Is the Evertune API ready for AI agents?

Evertune has a Kin Score of 29.4 out of 100 (thin) and an Agent Readiness score of 5.0 (human-only), scored by API Evangelist on 2026-11-06.

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