Mental health AI
Wysa
Wysa’s consumer self-help, institutional referral, and clinician-linked channels have different authority and data-sharing arrangements. This profile distinguishes those channels. The former combined score of 55 is historical, rather than a current score for every deployment.
Consumer, institutional and clinician-linked channels require distinct assessments. Historical scores are retained in the report.
Summary judgment · Unscored in current comparisons
Consumer, institutional and clinician-linked channels require distinct assessments. Historical axis: 55/100.
Mixed, channel-dependent
Wysa’s consumer self-help, institutional referral, and clinician-linked channels have different authority and data-sharing arrangements. This profile distinguishes those channels. The former combined score of 55 is historical, rather than a current score for every deployment.
Patient agency
How this tool changes agency
Exercises can support reflection and action. Clinical improvement is not a substitute for user control over routing, and formal data rights do not establish a direct appeal against a clinical decision.
Actual institutional signup notices, alternatives and review routes require deployment evidence
Patient agency assessment
Who sets and changes the goal?
Self-help users can redirect conversation. Institutional pathways constrain the offered resources, but the policy does not establish that the AI itself denies care or that declining it loses access.
What can the patient understand, question, or do?
Exercises can support reflection and action. Clinical improvement is not a substitute for user control over routing, and formal data rights do not establish a direct appeal against a clinical decision.
Can the patient evaluate the conditions of use?
Nickname-based consumer use must not imply anonymity across referral, WhatsApp or clinical deployments. External LLM no-training statements do not cover all internal improvement uses.
Text findings
Conditions of use
Published controls and their limits
Nickname-based consumer use must not imply anonymity across referral, WhatsApp or clinical deployments. External LLM no-training statements do not cover all internal improvement uses.
What remains unknown?
Not tested or not established
Actual institutional signup notices, alternatives and review routes require deployment evidence
Who evaluated this?
AI-assisted public-source draft
Vendor statements describe published conditions, not independently verified behavior. No clinical, security, accessibility, or legal validation is claimed. Earlier evidence remains dated in the report and history.
Sources checked
Source-specific findings and retrieval limitations are recorded in the full report.
Review provenance
Criteria
CAIHL-derived HugoScore framework and September 7 qualitative review priorities. Draft v1.2 numerical anchors remain unadopted.
Reviewer
AI-assisted public-source reassessment prepared in OpenAI Codex.
AI / model
OpenAI Codex / GPT-6
Human review
Hugo Campos authorized publication of these AI-assisted draft reassessments on September 8, 2026. This does not claim comprehensive human verification of every finding.
Review date
2026-09-08
Limitations
Actual institutional signup notices, alternatives and review routes require deployment evidence No live product use, patient-data upload, account creation, code audit, clinical evaluation, or independent implementation validation.
Review method
Focused public-source reassessment using CAIHL: patient authority, critical capacity, and informed control. Existing evidence plus one focused primary-source pass and at most one targeted follow-up. No live product testing. Numerical scores remain provisional editorial placements, not a new calculation.
Multiple deployments · Moderate for documented service distinctions (AI-assisted draft)