# Dragoneye

**Canonical:** https://apis.io/providers/dragoneye/  
**Website:** https://dragoneye.ai  
**APIs profiled:** 1

Dragoneye is a computer vision platform designed to democratize access to advanced image and video recognition technologies. It enables developers to build and deploy custom models tailored to their specific use cases without the need for coding or data labeling. By automating the entire process from model specification to deployment, Dragoneye eliminates the traditional complexities associated with computer vision development.

## Kin Score — 14.9 / 100 (emerging)

Scored 2026-08-21 under rubric 0.12.0. Trend: flat (+0.0 from 14.9).

| Facet | Score |
|---|---|
| Discoverability | 59.3 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 10.5 |
| Developer Ergonomics | 11.9 |
| Commercial Clarity | 26.3 |
| Access Clarity | 26.3 |

## Agent readiness — 3.0 (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 | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Freemium — onboarding: unknown, pricing: freemium, trial: no (confidence: medium).

## APIs (1)

- **Dragoneye API** — The Dragoneye API provides programmatic access to custom and prebuilt computer vision models for image and video recognition. Developers can classify images, detect objects, and...

## Security (1)

- **Dragoneye Domain Security** — TLSv1.3 · DMARC

## Plans (1)

- **Dragoneye Plans Pricing**

## Tags

Artificial Intelligence, Computer-Vision, Image Recognition, Video Recognition, Machine-Learning

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