# App-CM

**Canonical:** https://apis.io/providers/app-cm/  
**Website:** https://app-cm.co.jp  
**APIs profiled:** 0

App-CM, Inc. (株式会社アップシーエム) is a Tokyo-based technology company that operates a proprietary video-advertising delivery platform for smartphones, using in-house compression, delivery, and targeting-algorithm technology to serve video ads smoothly in mobile environments. App-CM also develops and publishes consumer mobile apps including FriendQuiz, SunQ, and Shakin. The company is backed by 500 Global and is profiled in the API Evangelist network. It ships a publisher-side iOS/Android video ad SDK, but distributes it only through a sales conversation: there is no public API, developer portal, SDK download, package-registry release, or machine-readable specification, and every /.well-known/ discovery path returns 404. This profile captures its identity, commercial model, and security posture.

## Kin Score — 10.8 / 100 (minimal)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 10.8).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 4.3 |
| Commercial Clarity | 21.1 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **App Cm Domain Security** — TLSv1.3

## Plans (1)

- **App Cm Plans Pricing**

## Tags

Company, Advertising, Video Advertising, AdTech, Mobile, Consumer Apps, Platform, Japan

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/app-cm/). Scores are computed from the provider's own public artifacts under a published rubric.