# huimei

**Canonical:** https://apis.io/providers/huimei/  
**Website:** https://www.huimei.com  
**APIs profiled:** 0

Huimei Technology (惠每科技) is a Chinese medical artificial intelligence company whose core hospital-facing platform, Dr.Mayson, delivers clinical decision support systems (CDSS) built on a curated medical knowledge base. Its product suite spans specialty CDSS, single-disease quality management and reporting, medical-record quality control, DRG/DIP insurance cost control, and VTE intelligent prevention, helping hospitals raise clinical quality and safety. Huimei is a portfolio company of Qiming Venture Partners. This profile was surfaced through the VC portfolio graph and enriched by the API Evangelist pipeline; the company publishes no public developer API program at this time.

## Kin Score — 3.3 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 3.3).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

Regulatory layer — **Health**: 7.5 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | 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)

- **Huimei Domain Security** — TLSv1.2

## Tags

Company, Healthcare, Medical AI, Clinical Decision Support, CDSS, Artificial Intelligence, Health IT, China

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