Faception

Faception is an Israeli facial personality analytics company that applies proprietary computer vision and machine learning to analyze facial images from photos, video streams, and cameras, scoring individuals against personality and behavioral classifiers. The company markets its technology to public-safety and smart-city security, fintech, retail, insurance, recruiting, and personal-robotics use cases, and states that it analyzes faces anonymously by storing mathematical classifiers rather than personal identity data. It was added to the API Evangelist network as a portfolio company of 500 Global; at this time it publishes a marketing site and blog but no public API, developer documentation, or machine-readable API surface.

Faception is profiled on the APIs.io network. Tagged areas include Company, Facial Recognition, Computer Vision, Machine Learning, and Biometrics.

Faception’s developer surface includes engineering blog and 2 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

3.4/100 minimal ▬ flat Agent 0/100 human only Front door AI 4/6 moderate Heartbeat 0/100 dormant Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs

Company Facial Recognition Computer Vision Machine Learning BiometricsPersonality AnalyticsPublic Safety Artificial Intelligence

Kin Score

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

Composite quality — 3.4/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 0.4 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 4.1 / 9

Regulatory Posture 0.8 / 15

Agent readiness — 0/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 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 AI & Biometrics 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
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
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

13 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
Access Clarity scores 0.0 — up to +20.0 composite points
Developer Ergonomics scores 2.4 — up to +19.5 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/faception/apis.yml: open an issue on github.com/api-evangelist/faception 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
Biometrics Testing (biometric recognition vendors, identity verification depth)	undeclared	-	-	1
ONVIF Video Analytics (video surveillance, edge cameras, computer vision)	undeclared	-	-	1

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.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Universal Commerce Protocol (UCP)

measured — observed by APIs.io (wix)

Security Posture 1

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

Faception Domain Security

TLSv1.3 · HSTS

SECURITY

Resources

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: faception
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:
  - security
  generated: '2026-11-06'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/faception.png
name: Faception
description: Faception is an Israeli facial personality analytics company that applies proprietary computer vision and machine
  learning to analyze facial images from photos, video streams, and cameras, scoring individuals against personality and behavioral
  classifiers. The company markets its technology to public-safety and smart-city security, fintech, retail, insurance, recruiting,
  and personal-robotics use cases, and states that it analyzes faces anonymously by storing mathematical classifiers rather
  than personal identity data. It was added to the API Evangelist network as a portfolio company of 500 Global; at this time
  it publishes a marketing site and blog but no public API, developer documentation, or machine-readable API surface.
url: https://raw.githubusercontent.com/api-evangelist/faception/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- 500-global
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Facial Recognition
- Computer Vision
- Machine Learning
- Biometrics
- Personality Analytics
- Public Safety
- Artificial Intelligence
tags_raw:
- Company
- Facial Recognition
- Computer Vision
- Machine Learning
- Biometrics
- Personality Analytics
- Public Safety
- Artificial Intelligence
- Computer-Vision
- Machine-Learning
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: DomainSecurity
  url: security/faception-domain-security.yml
- type: Website
  url: https://faception.com
- type: Blog
  url: https://www.faception.com/blog
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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