# HelixML

**Canonical:** https://apis.io/providers/helix-ml/  
**Website:** https://helix.ml/  
**APIs profiled:** 0

HelixML provides a platform for agent virtualization, enabling software teams to run isolated agent desktops on their own infrastructure. Their offerings include Helix GTM for sales teams, Helix Cyber for penetration testing, and Helix Recruiter to streamline hiring. The platform runs on Helix Cloud, Kubernetes, and Linux/macOS, emphasizing security with SOC 2, ISO 27001 compliance, and support for private AI platforms. It targets enterprises seeking to reduce toil, improve security, and accelerate development through scalable, isolated environments.

## Kin Score — 41.2 / 100 (developing)

Scored 2026-10-31 under rubric 0.25.0.

| Facet | Score |
|---|---|
| Discoverability | 44.6 |
| Contract Quality | 39.0 |
| Contract Governance | 18.2 |
| Operational Transparency | 7.9 |
| Developer Ergonomics | 50.0 |
| Access Clarity | 63.2 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 22.7 (matched via fallback).

## Agent readiness — 30.9 (agent-ready)

| Dimension | Value |
|---|---|
| Spec Presence | yes |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | served |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | yes |
| Agent Skills | no |
| Well Known Catalog | yes |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | served |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |

## Security (2)

- **Helix Ml Authentication** — 2 schemes
- **Helix Ml Domain Security** — TLSv1.3 · DMARC

## Plans (1)

- **Helix Ml Plans Pricing**

## Tags

Company, AI, Agent Virtualization, Security, Cloud

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