# Hone

**Canonical:** https://apis.io/providers/hone/  
**Website:** https://honehq.com  
**APIs profiled:** 0

Hone is an employee development platform that combines live, expert-led virtual workshops with AI-powered coaching to drive behavior change and continuous learning across an organization. Founded in 2018 and headquartered in San Francisco and New York City, Hone delivers 100+ live classes, AI lessons and roleplays, 1:1 and group coaching, and on-demand membership learning focused on leadership, management, and people skills. The platform integrates with major HRIS and LMS systems to sync learners and report on program impact, and has reached millions of employees across 58+ countries. Backed by F-Prime Capital, Cowboy Ventures, Slack Fund, and others. Hone does not currently publish a public developer API.

## Kin Score — 23.6 / 100 (emerging)

Scored 2026-08-17 under rubric 0.11.0. Trend: flat (+0.0 from 23.6).

| Facet | Score |
|---|---|
| Discoverability | 57.4 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Operational Transparency | 21.1 |
| Developer Ergonomics | 15.2 |
| Commercial Clarity | 60.5 |

## 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 (2)

- **Hone Domain Security** — TLSv1.3 · DMARC
- **Hone Trust Center** — SOC 2 Type 2, NIST AI RMF

## Tags

Company, Future Of Work, Leadership Development, Corporate Training, Learning And Development, Employee Development, Coaching, HR Technology, AI Coaching

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