Marker Learning website screenshot

Marker Learning

Marker Learning is a special-education technology company that provides AI-powered report-writing tools for school districts and evaluation teams. Its platform ingests referral and assessment documents and automatically drafts comprehensive psychological and educational evaluation reports, citing its sources for transparency, supporting multiple assessment and rating scales, and running built-in compliance checks. The company emphasizes FERPA and NIST CSF compliance. Marker Learning was surfaced as a portfolio company of a16z and added to the API Evangelist network. As of this enrichment pass it publishes no public API, developer portal, or API documentation.

Marker Learning is profiled on the APIs.io network. Tagged areas include Company, Education, Special Education, EdTech, and Assessment.

9.4/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyEducationSpecial EducationEdTechAssessmentArtificial IntelligenceReport Generation

Kin Score

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scored 2026-07-27 · rubric v0.5
Composite quality — 9.4/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.0 / 20
Commercial Clarity 2.6 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
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
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/marker-learning: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Security Posture 1

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

Marker Learning Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Access & Security 1

Authentication, authorization, and security posture

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: marker-learning
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/marker-learning.png
name: Marker Learning
description: Marker Learning is a special-education technology company that provides AI-powered report-writing tools for school
  districts and evaluation teams. Its platform ingests referral and assessment documents and automatically drafts comprehensive
  psychological and educational evaluation reports, citing its sources for transparency, supporting multiple assessment and
  rating scales, and running built-in compliance checks. The company emphasizes FERPA and NIST CSF compliance. Marker Learning
  was surfaced as a portfolio company of a16z and added to the API Evangelist network. As of this enrichment pass it publishes
  no public API, developer portal, or API documentation.
url: https://raw.githubusercontent.com/api-evangelist/marker-learning/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-20'
tags:
- Company
- Education
- Special Education
- EdTech
- Assessment
- Artificial Intelligence
- Report Generation
apis: []
common:
- type: DomainSecurity
  url: security/marker-learning-domain-security.yml
- type: Website
  url: https://www.markerlearning.com
- type: Login
  url: https://home.markerlearning.com
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-20'
  status: minimal
  artifacts_added: 1
  pass: local-v1