Zefr

Zefr is an ad-tech content intelligence company that classifies social video, image, audio and text so advertisers can buy and measure media against brand safety and suitability standards. Its classification engine labels content across YouTube, Meta (Facebook and Instagram), TikTok, Snapchat, Google Ads and DV360 against the 4A's and GARM frameworks, and its Brand Suitability Suite gives brands pre-bid controls and post-bid measurement from a single console. Zefr has no public developer program: production API infrastructure exists (api.zefr.com is a Google Apigee gateway, alongside api2.zefr.com and api-eu1.zefr.com) but no developer portal, API reference or machine-readable contract is published anywhere, and access runs through a demo request. The only machine-readable documents Zefr serves publicly are the OpenID Connect and OAuth 2.0 Authorization Server Metadata discovery documents on its Auth0 custom domain, login.zefr.com.

Zefr is profiled on the APIs.io network. Tagged areas include Company, AdTech, Brand Safety, Brand Suitability, and Content Intelligence.

Zefr’s developer surface includes authentication, support, engineering blog, and 17 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

21.4/100 emerging ▬ flat Agent 5/100 human only Front door AI 4/6 moderate Heartbeat 10/100 dormant saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessEnterprise

0 APIs

Company AdTech Brand SafetyBrand SuitabilityContent Intelligence Content Moderation Video Social Media Advertising Media Measurement Machine Learning

Kin Score

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

Composite quality — 21.4/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 3.2 / 17

Access Clarity 6.0 / 17

Operational Transparency 0.3 / 11

Contract Governance 1.9 / 10

Discoverability 4.1 / 9

Regulatory Posture 5.5 / 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 19.0 — up to +16.2 composite points
Access Clarity scores 35.5 — up to +12.9 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/zefr/apis.yml: open an issue on github.com/api-evangelist/zefr 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
TAG-Certified Ad Fraud and Brand Safety	standard	26.8 (thin)	-	-

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.

Zefr API pricing

Pricing Plans 1

Published pricing tiers and plan structures.

Zefr Plans Pricing

0 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Zefr Rate Limits

0 limits

RATE LIMITS

Security Posture 3

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

Zefr Authentication

2 schemes

SECURITY

Zefr Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Zefr Trust Center

read, published, note

SECURITY

Scopes 1

OAuth scopes governing access to this provider's APIs.

Zefr Scopes

14 scopes

SCOPES

Resources

Get Started 1

Portal, sign-up, and the first successful call

Login

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

WellKnown

WellKnown

LLMsTxt

LLMsTxt

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Lifecycle

Lifecycle

Build 2

SDKs, sample code, and the tooling you integrate with

Packages

Packages

GitHubOrganization

GitHubOrganization

Access & Security 5

Authentication, authorization, and security posture

DomainSecurity

TrustCenter

Authentication

OAuthScopes

Trust

Operate 2

Status, limits, changes, and where to get help

RateLimits

RateLimits

Support

Support

Commercial 3

Pricing, plans, and the legal terms of use

Plans

Plans

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

OpenIDConnect

OpenIDConnect

Source (apis.yml)

aid: zefr
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: enterprise
  onboarding: sales
  trial: false
  try_now: false
  public: false
  label: Enterprise / contact sales
  confidence: high
  source:
  - https://zefr.com/pricing
  - https://zefr.com/request-a-demo
  - https://suitability.zefr.com/
  generated: '2026-08-12'
  method: searched
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/zefr.png
name: Zefr
description: 'Zefr is an ad-tech content intelligence company that classifies social video, image, audio and text so advertisers
  can buy and measure media against brand safety and suitability standards. Its classification engine labels content across
  YouTube, Meta (Facebook and Instagram), TikTok, Snapchat, Google Ads and DV360 against the 4A''s and GARM frameworks, and
  its Brand Suitability Suite gives brands pre-bid controls and post-bid measurement from a single console. Zefr has no public
  developer program: production API infrastructure exists (api.zefr.com is a Google Apigee gateway, alongside api2.zefr.com
  and api-eu1.zefr.com) but no developer portal, API reference or machine-readable contract is published anywhere, and access
  runs through a demo request. The only machine-readable documents Zefr serves publicly are the OpenID Connect and OAuth 2.0
  Authorization Server Metadata discovery documents on its Auth0 custom domain, login.zefr.com.'
url: https://raw.githubusercontent.com/api-evangelist/zefr/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- felicis
- ivp
- uncork-capital
x-tier: stub
x-tier-reason: no-public-developer-program
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-08-12'
tags:
- Company
- AdTech
- Brand Safety
- Brand Suitability
- Content Intelligence
- Content Moderation
- Video
- Social Media
- Advertising
- Media Measurement
- Machine Learning
tags_raw:
- Company
- Adtech
- Brand Safety
- Brand Suitability
- Content Intelligence
- Content Moderation
- Video
- Social Media
- Advertising
- Media Measurement
- Machine Learning
- Social-Media
- Machine-Learning
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/zefr-plans-pricing.yml
- type: RateLimits
  url: rate-limits/zefr-rate-limits.yml
- type: DomainSecurity
  url: security/zefr-domain-security.yml
- type: TrustCenter
  url: security/zefr-trust-center.yml
- type: WellKnown
  url: well-known/zefr-well-known.yml
- type: OpenIDConnect
  url: well-known/zefr-openid-configuration.json
- type: Authentication
  url: authentication/zefr-authentication.yml
- type: OAuthScopes
  url: scopes/zefr-scopes.yml
- type: Conformance
  url: conformance/zefr-conformance.yml
- type: Lifecycle
  url: lifecycle/zefr-lifecycle.yml
- type: Packages
  url: packages/zefr-packages.yml
- type: LLMsTxt
  url: llms/zefr-llms.txt
- type: Website
  url: https://zefr.com
- type: Login
  url: https://suitability.zefr.com/
- type: Support
  url: https://zefr.com/contact-us
- type: Blog
  url: https://zefr.com/press
- type: GitHubOrganization
  url: https://github.com/ZEFR-INC
- type: TermsOfService
  url: https://zefr.com/terms-of-services
- type: PrivacyPolicy
  url: https://zefr.com/privacy-policy
- type: Trust
  url: https://trust.zefr.com/
x-enrichment:
  date: '2026-08-12'
  status: minimal
  artifacts_added: 12
  pass: local-v1
x-coverage:
  state: gated
  reason: sales-gate
  detail: Zefr runs live API infrastructure — api.zefr.com is a Google Apigee gateway that answers every anonymous request
    with a proprietary ApplicationNotFound fault — but publishes no developer portal, no API reference and no machine-readable
    contract; developer.zefr.com and docs.zefr.com do not resolve, the /support page renders the placeholder "Waiting on Content
    Entry...", and the only route to the platform is the "Request a Demo" form.
  evidence:
  - url: https://api.zefr.com/openapi.json
    status: 404
  - url: https://developer.zefr.com/
    status: 0
  - url: https://docs.zefr.com/
    status: 0
  - url: https://zefr.com/support
    status: 200
  - url: https://zefr.com/pricing
    status: 404
  - url: https://login.zefr.com/.well-known/openid-configuration
    status: 200
  checked: '2026-08-12'

Zefr API — frequently asked questions

How do I authenticate with the Zefr API?

Zefr uses bearer-token authentication (2 schemes). The details are profiled on APIs.io as Zefr Authentication.

Is the Zefr API ready for AI agents?

Zefr has a Kin Score of 21.4 out of 100 (emerging) and an Agent Readiness score of 5.0 (human-only), scored by API Evangelist on 2026-11-06.

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