# Healthmode

**Canonical:** https://apis.io/providers/healthmode/  
**APIs profiled:** 0

HealthMode was a machine-learning digital medicine company, founded in 2017 in San Francisco by Bradford Cross and Dan Karlin, that developed AI-enabled digital measurement methods to increase the precision and speed of clinical research. Its techniques improved phenotype understanding, streamlined screening and eligibility, enabled early detection of adverse events, and provided objective, low-burden efficacy endpoints for next-generation clinical trials. HealthMode was acquired by MindMed in 2021 and folded into MindMed's digital-medicine division (Albert); it no longer operates as an independent company, maintains no standalone website or public developer/API surface, and none of its former domains resolve.

## Kin Score — 2.2 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 2.2).

| 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**: 0.0 (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).

## Tags

Company, Digital Health, Clinical Trials, Digital Biomarkers, Machine-Learning, Digital Medicine, Life Sciences

---

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