Intrinsic website screenshot

Intrinsic

Intrinsic is a unified Trust & Safety platform that gives safety teams a single API and dashboard to detect, investigate, and enforce against abuse across user- and AI-generated content, fraud, and marketplace abuse. The platform surfaces machine-learning classifiers (for example text toxicity and IP trust scoring), account graph lineage for linkage analysis, geo enrichers, and global intelligence signals through a synchronous API, and lets teams author, version, deploy, and monitor real-time anti-abuse rules from a hosted dashboard. Founded in 2022 in San Francisco by Karine Mellata and Michael Lin (previously on Trust & Safety ML and data-engineering infrastructure at Apple and Discord), Intrinsic has since rebranded to Variance (variance.co); the Intrinsic-branded developer surfaces at docs.intrinsicapi.com and api.intrinsicapi.com remain in service.

Intrinsic publishes 1 API on the APIs.io network. Tagged areas include Company, Trust and Safety, Content Moderation, Anti-Abuse, and Fraud Prevention.

Intrinsic’s developer surface includes documentation and 7 more developer resources.

7.3/100 minimal ▬ flat Agent 0/100 human only Front door AI 5/6 prominent Full breakdown ↓
scored 2026-09-25 · rubric v0.23.0
1 APIs
CompanyTrust and SafetyContent ModerationAnti-AbuseFraud PreventionMachine LearningRisk Intelligence

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-25 · rubric v0.23.0
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/.
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 github.com/api-evangelist/intrinsic: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Intrinsic API

Unified Trust & Safety API exposing ML classifiers, enrichments, account graph lineage, and real-time rule evaluation for anti-abuse workflows. Access is gated behind an issued ...

Security Posture 2

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

Intrinsic Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Intrinsic Vulnerability Disclosure

security.txt · contact published

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Access & Security 4

Authentication, authorization, and security posture

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: intrinsic
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - url: https://withintrinsic.com
    status: 301
    note: declared website redirects to https://www.variance.com/ — a different registrable domain (withintrinsic.com -> variance.com),
      possible rename or acquisition (probed 2026-09-03, roadmap#169)
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/intrinsic.png
name: Intrinsic
description: Intrinsic is a unified Trust & Safety platform that gives safety teams a single API and dashboard to detect,
  investigate, and enforce against abuse across user- and AI-generated content, fraud, and marketplace abuse. The platform
  surfaces machine-learning classifiers (for example text toxicity and IP trust scoring), account graph lineage for linkage
  analysis, geo enrichers, and global intelligence signals through a synchronous API, and lets teams author, version, deploy,
  and monitor real-time anti-abuse rules from a hosted dashboard. Founded in 2022 in San Francisco by Karine Mellata and Michael
  Lin (previously on Trust & Safety ML and data-engineering infrastructure at Apple and Discord), Intrinsic has since rebranded
  to Variance (variance.co); the Intrinsic-branded developer surfaces at docs.intrinsicapi.com and api.intrinsicapi.com remain
  in service.
url: https://raw.githubusercontent.com/api-evangelist/intrinsic/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
x-tier: stub
x-tier-reason: portfolio-lead
x-rebranded-to: Variance
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Trust and Safety
- Content Moderation
- Anti-Abuse
- Fraud Prevention
- Machine Learning
- Risk Intelligence
tags_raw:
- Company
- Trust and Safety
- Content Moderation
- Anti-Abuse
- Fraud Detection
- Machine Learning
- Risk Intelligence
- API
- Machine-Learning
apis:
- name: Intrinsic API
  description: Unified Trust & Safety API exposing ML classifiers, enrichments, account graph lineage, and real-time rule
    evaluation for anti-abuse workflows. Access is gated behind an issued API key; developer documentation requires a request-access
    code.
  humanURL: https://docs.intrinsicapi.com/
  baseURL: https://api.intrinsicapi.com
  properties:
  - type: Documentation
    url: https://docs.intrinsicapi.com/
  - type: GettingStarted
    url: https://docs.intrinsicapi.com/getting-started/welcome
common:
- type: Website
  url: https://withintrinsic.com
- type: DeveloperPortal
  url: https://docs.intrinsicapi.com/
- type: Documentation
  url: https://docs.intrinsicapi.com/
- type: SecurityTxt
  url: well-known/intrinsic-security.txt
- type: WellKnown
  url: well-known/intrinsic-well-known.yml
- type: VulnerabilityDisclosure
  url: security/intrinsic-vulnerability-disclosure.yml
- type: Security
  url: security/intrinsic-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/intrinsic-domain-security.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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